diff --git a/_includes/schedule/_general.html b/_includes/schedule/_general.html index 2e6c509..d6142b0 100644 --- a/_includes/schedule/_general.html +++ b/_includes/schedule/_general.html @@ -272,6 +272,7 @@

Sunday – September 8

Maasai Mara no recording Tsavo Hall no recording Amboseli Hall no recording + Pre-recorded Lightning Talks no recording @@ -290,7 +291,7 @@

Sunday – September 8

Get to know OSGeo and expand Your Open Mapping Toolkit
Laura Mugeha - + 10:00 @@ -302,7 +303,7 @@

Sunday – September 8


Wangshu Wang - + 10:30 @@ -314,10 +315,10 @@

Sunday – September 8


Achituv Cohen - + 11:00 - Coffee Break + Coffee Break 11:30 @@ -329,7 +330,7 @@

Sunday – September 8

The worst and best of OpenStreetMap in Ghana (Africa)
Enock Seth Nyamador - + 12:00 @@ -341,7 +342,7 @@

Sunday – September 8


Benjamin Herfort - + 12:30 @@ -353,10 +354,10 @@

Sunday – September 8


Alex Hoferek - + 13:00 - Lunch + Lunch 14:30 @@ -368,7 +369,7 @@

Sunday – September 8

From Source to Map: Strategies for Integrating External Data into OpenStreetMap
Amour Nyalusi - + 15:00 @@ -380,7 +381,7 @@

Sunday – September 8


Marco Minghini, Yair Grinberger - + 15:30 @@ -388,10 +389,10 @@

Sunday – September 8


Paweł Struś - + 16:00 - Coffee and Snacks + Coffee and Snacks 16:30 @@ -399,7 +400,14 @@

Sunday – September 8

Closing Session
SotM Working Group - + + + 17:00 + + Pre-recorded Lightning Talks
SotM Working Group + + + diff --git a/img/video-previews/video-8ZVKZV.jpeg b/img/video-previews/video-8ZVKZV.jpeg new file mode 100644 index 0000000..6b42b13 Binary files /dev/null and b/img/video-previews/video-8ZVKZV.jpeg differ diff --git a/img/video-previews/video-CDT3PZ.jpeg b/img/video-previews/video-CDT3PZ.jpeg new file mode 100644 index 0000000..eaef57e Binary files /dev/null and b/img/video-previews/video-CDT3PZ.jpeg differ diff --git a/img/video-previews/video-FSYR9S.jpeg b/img/video-previews/video-FSYR9S.jpeg new file mode 100644 index 0000000..2238af0 Binary files /dev/null and b/img/video-previews/video-FSYR9S.jpeg differ diff --git a/img/video-previews/video-HD9RQD.jpeg b/img/video-previews/video-HD9RQD.jpeg new file mode 100644 index 0000000..b6da55d Binary files /dev/null and b/img/video-previews/video-HD9RQD.jpeg differ diff --git a/img/video-previews/video-LAZXYU.jpeg b/img/video-previews/video-LAZXYU.jpeg new file mode 100644 index 0000000..3abe12f Binary files /dev/null and b/img/video-previews/video-LAZXYU.jpeg differ diff --git a/img/video-previews/video-MKPJFW.jpeg b/img/video-previews/video-MKPJFW.jpeg new file mode 100644 index 0000000..a87b94b Binary files /dev/null and b/img/video-previews/video-MKPJFW.jpeg differ diff --git a/img/video-previews/video-NQHRLV.jpeg b/img/video-previews/video-NQHRLV.jpeg new file mode 100644 index 0000000..d4cde65 Binary files /dev/null and b/img/video-previews/video-NQHRLV.jpeg differ diff --git a/img/video-previews/video-PG3K3G.jpeg b/img/video-previews/video-PG3K3G.jpeg new file mode 100644 index 0000000..312d3e4 Binary files /dev/null and b/img/video-previews/video-PG3K3G.jpeg differ diff --git a/img/video-previews/video-R9CVQD.jpeg b/img/video-previews/video-R9CVQD.jpeg new file mode 100644 index 0000000..21ed2c6 Binary files /dev/null and b/img/video-previews/video-R9CVQD.jpeg differ diff --git a/img/video-previews/video-SHA79S.jpeg b/img/video-previews/video-SHA79S.jpeg new file mode 100644 index 0000000..fda8574 Binary files /dev/null and b/img/video-previews/video-SHA79S.jpeg differ diff --git a/img/video-previews/video-TXYEFS.jpeg b/img/video-previews/video-TXYEFS.jpeg new file mode 100644 index 0000000..1384abb Binary files /dev/null and b/img/video-previews/video-TXYEFS.jpeg differ diff --git a/img/video-previews/video-TY73TC.jpeg b/img/video-previews/video-TY73TC.jpeg new file mode 100644 index 0000000..8dfae50 Binary files /dev/null and b/img/video-previews/video-TY73TC.jpeg differ diff --git a/img/video-previews/video-VFUBCD.jpeg b/img/video-previews/video-VFUBCD.jpeg new file mode 100644 index 0000000..72e2b07 Binary files /dev/null and b/img/video-previews/video-VFUBCD.jpeg differ diff --git a/sessions/8ZVKZV.md b/sessions/8ZVKZV.md index 4c20e1d..e7256e0 100644 --- a/sessions/8ZVKZV.md +++ b/sessions/8ZVKZV.md @@ -1,4 +1,7 @@ --- +youtube: jERUxuccM5E +voc: https://media.ccc.de/v/sotm2024-50902-closing-session +recordings: [{'size': 247, 'length': 1774, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50902-eng-Closing_Session_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T20:14:51.959+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50902-eng-Closing_Session_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82050', 'event_url': 'https://api.media.ccc.de/public/events/727120ec-6cb7-53c0-9817-141cac6e1f10', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 90, 'length': 1774, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50902-eng-Closing_Session_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:51:09.136+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50902-eng-Closing_Session_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82049', 'event_url': 'https://api.media.ccc.de/public/events/727120ec-6cb7-53c0-9817-141cac6e1f10', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 27, 'length': 1774, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50902-eng-Closing_Session_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-29T19:26:55.500+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50902-eng-Closing_Session_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82046', 'event_url': 'https://api.media.ccc.de/public/events/727120ec-6cb7-53c0-9817-141cac6e1f10', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 93, 'length': 1774, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50902-eng-Closing_Session_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:26:51.722+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50902-eng-Closing_Session_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82045', 'event_url': 'https://api.media.ccc.de/public/events/727120ec-6cb7-53c0-9817-141cac6e1f10', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 362, 'length': 1774, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50902-eng-Closing_Session_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T19:20:54.001+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50902-eng-Closing_Session_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82042', 'event_url': 'https://api.media.ccc.de/public/events/727120ec-6cb7-53c0-9817-141cac6e1f10', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Closing Session" code: "8ZVKZV" diff --git a/sessions/CDT3PZ.md b/sessions/CDT3PZ.md index 394e011..8f11ce1 100644 --- a/sessions/CDT3PZ.md +++ b/sessions/CDT3PZ.md @@ -1,4 +1,7 @@ --- +youtube: y8be0eS2UcQ +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50699-beyond-the-seventh-mountain-beyond-the-seventh-river-openstreetmap-as-a-base-map-in-geographical-research +recordings: [{'size': 118, 'length': 1517, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T19:46:57.248+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82048', 'event_url': 'https://api.media.ccc.de/public/events/dbc90072-eea8-5c08-87a3-8f574211c190', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 54, 'length': 1517, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:23:56.000+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82044', 'event_url': 'https://api.media.ccc.de/public/events/dbc90072-eea8-5c08-87a3-8f574211c190', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 23, 'length': 1517, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-29T19:16:14.485+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82041', 'event_url': 'https://api.media.ccc.de/public/events/dbc90072-eea8-5c08-87a3-8f574211c190', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 36, 'length': 1517, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:13:44.206+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82040', 'event_url': 'https://api.media.ccc.de/public/events/dbc90072-eea8-5c08-87a3-8f574211c190', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 95, 'length': 1517, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T19:02:04.655+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50699-eng-Beyond_the_seventh_mountain_beyond_the_seventh_river_-_Openstreetmap_as_a_base_map_in_geographical_research_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82035', 'event_url': 'https://api.media.ccc.de/public/events/dbc90072-eea8-5c08-87a3-8f574211c190', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Beyond the seventh mountain, beyond the seventh river - Openstreetmap as a base map in geographical research" code: "CDT3PZ" @@ -12,22 +15,22 @@ resources: [{ description: "Presentation slides", url: "https://pretalx.com/medi recording: False --- -Openstreet map has for a long time been treated as a road map, enabling you to find a route between two points, as well as an information map, gathering various points of interests. +Openstreet map has for a long time been treated as a road map, enabling you to find a route between two points, as well as an information map, gathering various points of interests. Together with students of the UKEN University from Krakow, we decided to look at the use of OSM as a environmental map also showing the transformation of space by humans.
-The speech is the result of exercises conducted by employees of the Geoinformation Research Team and students of the UKEN University in Krakow, Poland. The basic assumption we made is that OpenStreetMap can be sufficient as a data provider for various geographical works - as a base map for field exercises, as an almost complete environmental database for some compact area (such as an island or a national park). After reviewing the list of tags describing the geographic environment in OSM, we knew this would be possible. We have selected several research polygons, which we call cartographic polygons. These include the Peljesac Peninsula in Croatia, the Aegean Coast near Thessaloniki in Greece, the area around Lake Inari, the Lemenjoki National Park in Finland, and the wild Bieszczady Mountains in Poland. We selected the training fields so that they were both places with nature close to natural conditions and places significantly transformed by human activity. Usually, these were also important places for some key reasons - for example, on the Peljesac Peninsula, a bridge was built to facilitate communication between the two parts of Dalmatia. Not all places were visited, but we have collected cartographic material for all of them. Before each trip, we trained a group of participants on how to use and supplement OSM. Each participant set up their own user account. Field work consisted of completing the content of OpenstreetMap as accurately as possible - groups of two people were sent into the field and, using the OSMAND or EveryDoor applications, they inserted all interesting objects on the map. The rest is small-scale work - tedious verification and editing of the map in the JOSM editor. -Each stage of work was also preceded by a thorough analysis of official OSM tags - which constitute information about all elements of the natural environment. It was found that the best represented features were those related to relief, land cover and hydrology. In particular, the content regarding land cover (down to a single tree and bush), and the richness of descriptions of relief forms (OSM WIKI, Glossary of landforms) allow the creation of appropriate thematic maps - landcover maps and geomorphological maps. - -The principle adopted in JOSM is that we complete the map to the highest degree of accuracy possible using available data and processing capacity. For example, we supplement the terrain coverage for Poland from the available official orthophotomap from the national geoportal with a terrain resolution of 5 cm. The distinction between land cover types is made by students of higher years of geography, so there should not be too many interpretation errors. -What information is completed on the map? As for the relief of the land - valleys and valley types, rock walls, erosion undercuts, landslides and landslide niches. When it comes to hydrological elements, using scientific publications, we entered the exact location of the sources (along with a description of water chemistry and name, if this data was available). -An additional module of our work is urban micromapping - We check how accurately we can supplement field data so that they can serve two purposes - for students and spatial planning specialists in the analysis and inventory of urban space, and for people with disabilities as a base for accessibility maps used in applications, e.g. blind . For this purpose, we carried out tests of terrain mapping using a geodetic GPS receiver (STONEX 900A). We chose the area on the campus of our university due to the presence of the remains of an old water bed supplying water to mills and a city moat - a lot of unevenness, steps, suddenly ending sidewalks, etc. -Additionally, we have also started work on old housing estates in Krakow's Nowa Huta district - inhabited mainly by older people, and therefore often beneficiaries of all programs regarding the availability of public facilities and apartments. -Approximately one thousand points were measured in the above locations with an accuracy of 2 mm - 1 cm. In further stages, they will serve as the basis for the point cloud made during unmanned aerial vehicle raids. -A number of additional works were also carried out as part of the project, e.g. wild waste dumps in the Ojców National Park were mapped and marked (we will most likely use the tag amenity=waste_dump_site) - -All work on the project resulted not only in a significant improvement in the quality of the OSM map, but also in the training of a large team who, in their free time, complete OSM data in their area. -Both the intimate and field parts of the work are still in progress. We will complete the work by the time of the presentation in Nairobi. +The speech is the result of exercises conducted by employees of the Geoinformation Research Team and students of the UKEN University in Krakow, Poland. The basic assumption we made is that OpenStreetMap can be sufficient as a data provider for various geographical works - as a base map for field exercises, as an almost complete environmental database for some compact area (such as an island or a national park). After reviewing the list of tags describing the geographic environment in OSM, we knew this would be possible. We have selected several research polygons, which we call cartographic polygons. These include the Peljesac Peninsula in Croatia, the Aegean Coast near Thessaloniki in Greece, the area around Lake Inari, the Lemenjoki National Park in Finland, and the wild Bieszczady Mountains in Poland. We selected the training fields so that they were both places with nature close to natural conditions and places significantly transformed by human activity. Usually, these were also important places for some key reasons - for example, on the Peljesac Peninsula, a bridge was built to facilitate communication between the two parts of Dalmatia. Not all places were visited, but we have collected cartographic material for all of them. Before each trip, we trained a group of participants on how to use and supplement OSM. Each participant set up their own user account. Field work consisted of completing the content of OpenstreetMap as accurately as possible - groups of two people were sent into the field and, using the OSMAND or EveryDoor applications, they inserted all interesting objects on the map. The rest is small-scale work - tedious verification and editing of the map in the JOSM editor. +Each stage of work was also preceded by a thorough analysis of official OSM tags - which constitute information about all elements of the natural environment. It was found that the best represented features were those related to relief, land cover and hydrology. In particular, the content regarding land cover (down to a single tree and bush), and the richness of descriptions of relief forms (OSM WIKI, Glossary of landforms) allow the creation of appropriate thematic maps - landcover maps and geomorphological maps. + +The principle adopted in JOSM is that we complete the map to the highest degree of accuracy possible using available data and processing capacity. For example, we supplement the terrain coverage for Poland from the available official orthophotomap from the national geoportal with a terrain resolution of 5 cm. The distinction between land cover types is made by students of higher years of geography, so there should not be too many interpretation errors. +What information is completed on the map? As for the relief of the land - valleys and valley types, rock walls, erosion undercuts, landslides and landslide niches. When it comes to hydrological elements, using scientific publications, we entered the exact location of the sources (along with a description of water chemistry and name, if this data was available). +An additional module of our work is urban micromapping - We check how accurately we can supplement field data so that they can serve two purposes - for students and spatial planning specialists in the analysis and inventory of urban space, and for people with disabilities as a base for accessibility maps used in applications, e.g. blind . For this purpose, we carried out tests of terrain mapping using a geodetic GPS receiver (STONEX 900A). We chose the area on the campus of our university due to the presence of the remains of an old water bed supplying water to mills and a city moat - a lot of unevenness, steps, suddenly ending sidewalks, etc. +Additionally, we have also started work on old housing estates in Krakow's Nowa Huta district - inhabited mainly by older people, and therefore often beneficiaries of all programs regarding the availability of public facilities and apartments. +Approximately one thousand points were measured in the above locations with an accuracy of 2 mm - 1 cm. In further stages, they will serve as the basis for the point cloud made during unmanned aerial vehicle raids. +A number of additional works were also carried out as part of the project, e.g. wild waste dumps in the Ojców National Park were mapped and marked (we will most likely use the tag amenity=waste_dump_site) + +All work on the project resulted not only in a significant improvement in the quality of the OSM map, but also in the training of a large team who, in their free time, complete OSM data in their area. +Both the intimate and field parts of the work are still in progress. We will complete the work by the time of the presentation in Nairobi. This is our beginning in the work of OpenstreetMap, but we would like to use our previous experience in completing OSM data in various places around the world in many task programs, e.g. for UN Mappers and HOT OSM. Best regards form Poland. diff --git a/sessions/FSYR9S.md b/sessions/FSYR9S.md index 87a6f7d..7e32f46 100644 --- a/sessions/FSYR9S.md +++ b/sessions/FSYR9S.md @@ -1,4 +1,7 @@ --- +youtube: FeXq2NZ2IK4 +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50780-what-happens-when-vgi-is-threatened-a-systems-perspective-analysis-of-the-events-behind-the-introduction-of-rate-limiting-in-openstreetmap +recordings: [{'size': 111, 'length': 1743, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T19:43:41.890+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82047', 'event_url': 'https://api.media.ccc.de/public/events/d61461c8-e97f-507c-9af3-9e167d7986b1', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 56, 'length': 1743, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:21:15.565+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82043', 'event_url': 'https://api.media.ccc.de/public/events/d61461c8-e97f-507c-9af3-9e167d7986b1', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 26, 'length': 1743, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-29T19:06:53.246+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82038', 'event_url': 'https://api.media.ccc.de/public/events/d61461c8-e97f-507c-9af3-9e167d7986b1', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 41, 'length': 1743, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:06:49.410+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82037', 'event_url': 'https://api.media.ccc.de/public/events/d61461c8-e97f-507c-9af3-9e167d7986b1', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 91, 'length': 1743, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T19:00:02.716+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50780-eng-What_happens_when_VGI_is_threatened_A_systems_perspective_analysis_of_the_events_behind_the_introduction_of_rate_limiting_in_OpenStreetMap_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82034', 'event_url': 'https://api.media.ccc.de/public/events/d61461c8-e97f-507c-9af3-9e167d7986b1', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "What happens when VGI is threatened? A systems perspective analysis of the events behind the introduction of rate limiting in OpenStreetMap" code: "FSYR9S" @@ -16,9 +19,9 @@ This talk presents a systems perspective analysis of events in October-November
-OpenStreetMap (OSM) is generally considered to be a ‘do-ocracy’ [1], a governing system in which power stems from doing and those who do more (contribute more) have greater ability to influence the project. This does not mean that hierarchy within OSM is entirely bottom-up, as Fast & Rimmer’s systems perspective model of a Volunteered Geographic Information project suggests [2] - it is made of interconnected components (the technical infrastructure, project, and contributors) each providing a different level of direct access to the core of the project. Entities may move between these components, but a certain level of separation still exists, enforced informally or formally by gatekeeping procedures or individual acts. The fuzziness of borders and the interdependence of components open for multiple types of interactions that may translate to major impacts on the nature of the project. In this talk we use communication records from various media (the OSM_Israel Telegram group [3], community forum discussions [4,5], and GitHub issues [6,7]) to: i) to analyse a specific set of events - the politically-motivated edits in Israel and the subsequent introduction of rate limiting in OSM [8] - from a systems perspective; and ii) conceptually explore power dynamics and impacts within collaborative geodata projects and specifically OSM along with their implications for the project’s vulnerability and resilience. -The chain of events started on 20 October 2023, when two members of the OSM_Israel Telegram group [3] reported receiving offensive comments on their recent edits. One of them noted that the commenting user was performing edits to the OSM data in Israel that were clearly acts of vandalism, i.e. deleting and distorting data. It was only the day after that the members of the Telegram group realised that these acts were part of a greater effort in which 3 newly registered OSM users were performing large-scale deletions and distortions of data in Israel. The timing of these edits, taking place while the Israel Defense Forces were launching airstrikes over Gaza strip in retaliation of the 7 October attack by Hamas, and their related changeset comments, e.g. “There is no country Israel & Free Palestine”, clearly attested that they were politically-motivated (For a representative example, see [9]). The events were quickly reported to the OSM Foundation’s (OSMF) Data Working Group (DWG), the voluntary body responsible for handling data issues such as copyright infringement and vandalism. The DWG issued bans to involved users, yet these were replaced in the next few days by more new users together making tens of thousands of similar edits. Meanwhile, one user, responding to these acts, further vandaled the map by ‘annexing’ part of the Gaza strip [10]. - In the immediate aftermath of these events, most of the OSM data for Tel Aviv was deleted from the map and data all across Israel and the eastern Mediterranean basin, as far as Crete, Cyprus, and Turkey, suffered from distortions (the scripts the vandal accounts were using automatically distorted random objects crossing the area of Israel, including objects such as coastlines that extend beyond these boundaries). Yet the impacts of the events did not end with the DWG reverting the vandal edits. These events had a direct connection with the introduction of a daily rate limit (set individually based on the seniority of the editing user and the number of edited entities, among other things [8]). The idea of such a limit had already existed for a while and was discussed within dedicated GitHub issues [6,7], yet it was only after members of the Israeli OSM community had commented within these issues and in a related community forum discussion [5] that the notion had been implemented. Interestingly, a DWG member which was handling the bans and reverts was the one who referenced the Israeli community to the forum discussion - in response to a question raised in the Israeli Telegram about whether any measures have been implemented to ensure this would not happen again, this user had suggested that they will ask that question in the relevant forum discussion. -As extreme as this vandalism case was in comparison to other acts of vandalism or politically-motivated edits, its outcome tells a story regarding the fluidity of power dynamics within the project and accordingly - its vulnerability- and resilience-inducing mechanisms. The enforcement of rate limiting required a temporary coalition between individuals within the contributors and project components, where DWG members used the ‘traditional’ crossing path - from project to contributors, i.e. the DWG engaging with contributions to the point of joining the Telegram group - to mobilise support for their cause by encouraging contributors to engage with the management of the project, i.e. joining the GitHub discussion on rate limiting. This collaboration was in turn enabled by a joint sense of urgency stemming from the vandals violating the basic assumptions required for OSM to function - shared goals, adherence to community procedures, and mapping limited to verifiable objects. On the one hand, the temporary coalition formed between the local OSM community and the DWG members shows that the fuzzy nature of component boundaries allows for flexibility that enhances resilience in the sense of the ability to reorganise and adapt when conditions change. However, it shows that even temporary coalitions (it is useful to remember the Israeli community’s dissatisfaction with how the DWG handled the Jerusalem node issue [11]) of a handful of people reacting to a local event can lead to a global change occurring without a general consensus within the community (some dissatisfaction with the decision was already expressed [12,13]). If this becomes a common practice, it may undermine the stability of community procedures within OSM, especially if disagreements emerge due to clashing interests. +OpenStreetMap (OSM) is generally considered to be a ‘do-ocracy’ [1], a governing system in which power stems from doing and those who do more (contribute more) have greater ability to influence the project. This does not mean that hierarchy within OSM is entirely bottom-up, as Fast & Rimmer’s systems perspective model of a Volunteered Geographic Information project suggests [2] - it is made of interconnected components (the technical infrastructure, project, and contributors) each providing a different level of direct access to the core of the project. Entities may move between these components, but a certain level of separation still exists, enforced informally or formally by gatekeeping procedures or individual acts. The fuzziness of borders and the interdependence of components open for multiple types of interactions that may translate to major impacts on the nature of the project. In this talk we use communication records from various media (the OSM_Israel Telegram group [3], community forum discussions [4,5], and GitHub issues [6,7]) to: i) to analyse a specific set of events - the politically-motivated edits in Israel and the subsequent introduction of rate limiting in OSM [8] - from a systems perspective; and ii) conceptually explore power dynamics and impacts within collaborative geodata projects and specifically OSM along with their implications for the project’s vulnerability and resilience. +The chain of events started on 20 October 2023, when two members of the OSM_Israel Telegram group [3] reported receiving offensive comments on their recent edits. One of them noted that the commenting user was performing edits to the OSM data in Israel that were clearly acts of vandalism, i.e. deleting and distorting data. It was only the day after that the members of the Telegram group realised that these acts were part of a greater effort in which 3 newly registered OSM users were performing large-scale deletions and distortions of data in Israel. The timing of these edits, taking place while the Israel Defense Forces were launching airstrikes over Gaza strip in retaliation of the 7 October attack by Hamas, and their related changeset comments, e.g. “There is no country Israel & Free Palestine”, clearly attested that they were politically-motivated (For a representative example, see [9]). The events were quickly reported to the OSM Foundation’s (OSMF) Data Working Group (DWG), the voluntary body responsible for handling data issues such as copyright infringement and vandalism. The DWG issued bans to involved users, yet these were replaced in the next few days by more new users together making tens of thousands of similar edits. Meanwhile, one user, responding to these acts, further vandaled the map by ‘annexing’ part of the Gaza strip [10]. + In the immediate aftermath of these events, most of the OSM data for Tel Aviv was deleted from the map and data all across Israel and the eastern Mediterranean basin, as far as Crete, Cyprus, and Turkey, suffered from distortions (the scripts the vandal accounts were using automatically distorted random objects crossing the area of Israel, including objects such as coastlines that extend beyond these boundaries). Yet the impacts of the events did not end with the DWG reverting the vandal edits. These events had a direct connection with the introduction of a daily rate limit (set individually based on the seniority of the editing user and the number of edited entities, among other things [8]). The idea of such a limit had already existed for a while and was discussed within dedicated GitHub issues [6,7], yet it was only after members of the Israeli OSM community had commented within these issues and in a related community forum discussion [5] that the notion had been implemented. Interestingly, a DWG member which was handling the bans and reverts was the one who referenced the Israeli community to the forum discussion - in response to a question raised in the Israeli Telegram about whether any measures have been implemented to ensure this would not happen again, this user had suggested that they will ask that question in the relevant forum discussion. +As extreme as this vandalism case was in comparison to other acts of vandalism or politically-motivated edits, its outcome tells a story regarding the fluidity of power dynamics within the project and accordingly - its vulnerability- and resilience-inducing mechanisms. The enforcement of rate limiting required a temporary coalition between individuals within the contributors and project components, where DWG members used the ‘traditional’ crossing path - from project to contributors, i.e. the DWG engaging with contributions to the point of joining the Telegram group - to mobilise support for their cause by encouraging contributors to engage with the management of the project, i.e. joining the GitHub discussion on rate limiting. This collaboration was in turn enabled by a joint sense of urgency stemming from the vandals violating the basic assumptions required for OSM to function - shared goals, adherence to community procedures, and mapping limited to verifiable objects. On the one hand, the temporary coalition formed between the local OSM community and the DWG members shows that the fuzzy nature of component boundaries allows for flexibility that enhances resilience in the sense of the ability to reorganise and adapt when conditions change. However, it shows that even temporary coalitions (it is useful to remember the Israeli community’s dissatisfaction with how the DWG handled the Jerusalem node issue [11]) of a handful of people reacting to a local event can lead to a global change occurring without a general consensus within the community (some dissatisfaction with the decision was already expressed [12,13]). If this becomes a common practice, it may undermine the stability of community procedures within OSM, especially if disagreements emerge due to clashing interests. Beyond this specific insight, this case allows mapping out different axes of power dynamics within OSM - the stakeholders (i.e. the system components), the crossing paths (e.g. project-to-contributors, contributors-to-infrastructure), the sources of capital (e.g. the masses, the project, access to resources and/or infrastructure), the nature of crossing (e.g. invitation, infiltration, takeover, acquisition), and motivations (e.g. individual/communal interests, safeguarding the project, values). Characterising other cases of external or semi-external engagement with OSM in light of these, e.g. corporate engagement with OSM, the collaboration of Meta and HOT (The Humanitarian OSM Team), and the development of Rapid, can produce insights on their deeper implications for the project and help imagine future paths of influence and their impacts. diff --git a/sessions/HD9RQD.md b/sessions/HD9RQD.md index 167170e..46073dc 100644 --- a/sessions/HD9RQD.md +++ b/sessions/HD9RQD.md @@ -1,4 +1,7 @@ --- +youtube: A9vcqolx_h0 +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50244-shifting-trends-in-global-evolution-of-corporate-mapping-in-osm +recordings: [{'size': 119, 'length': 1541, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T21:06:57.352+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82028', 'event_url': 'https://api.media.ccc.de/public/events/246553bf-6351-5e15-a369-54ffc09f458c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 59, 'length': 1541, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:49:56.037+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82023', 'event_url': 'https://api.media.ccc.de/public/events/246553bf-6351-5e15-a369-54ffc09f458c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 42, 'length': 1541, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:39:31.676+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82020', 'event_url': 'https://api.media.ccc.de/public/events/246553bf-6351-5e15-a369-54ffc09f458c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 23, 'length': 1541, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-28T20:38:13.715+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82018', 'event_url': 'https://api.media.ccc.de/public/events/246553bf-6351-5e15-a369-54ffc09f458c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 100, 'length': 1541, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T20:35:35.281+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50244-eng-Shifting_trends_in_global_evolution_of_corporate_mapping_in_OSM_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82016', 'event_url': 'https://api.media.ccc.de/public/events/246553bf-6351-5e15-a369-54ffc09f458c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Shifting trends in global evolution of corporate mapping in OSM" code: "HD9RQD" @@ -16,35 +19,35 @@ This talk will look at corporate editing in OSM at three scales - global, nation
-Introduction: - -In recent years, with the emergence of corporate editing in OpenStreetMap (OSM), there has been interest, and in some cases concern, about its influence in OSM. For instance, large corporations like such as Apple, Microsoft, Meta and Amazon have hired large teams to edit in OSM ​[1]. The launch of the Overture Maps Foundation, by Amazon, Meta, Microsoft and TomTom hosted by the Linux Foundation in 2022 and the release of its first dataset [2] has also led to heated debates on the OSM forum, regarding the future of OSM. Concerns have been raised about the monopolisation of geodata, the replacement of OSM by other sites or the backlining of OSM [3]. - -Consequently, analysing and continuously monitoring the impact of corporate contributors and continuing to observe their fluctuating patterns of editing will be significant to the understanding of the sustainability of OSM. Therefore, this talk will look at corporate editing in OSM at three scales - global, national and local to answer the two research questions: - -(RQ1) What is the impact of corporate mapping on global scale mapping? - -(RQ2) What is the impact of corporate mapping on country and small-scale mapping? - -Methodology: - -There are two main avenues to track corporate contributors: Either through corporate affiliated OSM User IDs (UIDs) or through corporate hashtags in OSM changesets. UIDs of corporation affiliated mappers have been used in the past to track corporate activity in OSM (e.g. [1, 4, 5]). A list of affiliated usernames can be collected from disclosed lists on the OSM Wiki or corporations GitHub pages [6]. The second way to track corporate edits is through corporate hashtags in changesets. Since 2009, it became possible to add hashtags to changesets in OSM, and this has become common practice, especially to show affiliation to regions, events, organisations or corporations [7]. For the analysis presented here, in total 24 companies were tracked including Apple, Kaart, Amazon, Microsoft, TomTom, Grab, DigitalEgypt, Mapbox and Meta. We used tracking with hashtags was used as proposed by [7]. - -The dataset used for the analysis integrated data from two sources: The OpenStreetMap History Database [8] and the OSM Changeset database. The OSHDB was used to derive OSM geometries and attribute information as well as information about the editors. The data was then intersected with a dataset of country boundaries to assign a mapping to a specific country. The OSM changeset dataset was joined to this contribution dataset. The dataset included a plethora of information, but the most relevant columns for the analysis were the OSM ID, Changeset timestamp, hashtags and User IDs, country, year and month as well as the geometry information – including the centroids. (We aim at presenting this dataset in detail in another workshop at SOTM 2024.) - -At the global level, two analyses were carried out. First, the temporal development of corporate and total edits from 2016-01-01 – 2023-12-31, including a breakdown by individual corporation. Second, the absolute number of corporate edits per country and the percentage of corporate edits based on total edits per country for the period 2019-06-01 to 2023-05-31 were analyzed. For an additional overview, the country-level results were grouped by Human Development Index (HDI) class, for a more in depth understanding of the spatial distribution of corporate edits in respect to socio-economic factors. - -Countries with more than 15% corporate edits and more than 100,000 total edits in this period were selected for an in-depth analysis. A total of 28 countries met these requirements and we extracted the monthly corporate and non-corporate edits. The overall timeframe for analysis was divided into two time periods: t0 (2019-06-01– 2021-05-31) and t1 (2021-06-01 – 2023-05-31). For each country we derived the change in average activity for both corporate and non-corporate mapping. - -Three countries were selected from the 28 countries with high corporate mapping activity for the small-scale analysis: Colombia, Indonesia and the United Arab Emirates. For these countries we produced a high-resolution spatial dataset based on a H3 grid utilizing the centroid geometry of each OSM contribution. We performed a spatial auto-correlation analysis to identify regions where corporate (and non-corporate) edits have increased / declined over the past years. In addition to the maps, a normalized confusion matrix was calculated to compare the spatial autocorrelation results and present the overlap or difference between the trends in corporate and non-corporate mapping. - -Results and Discussion: - -At the global scale (RQ1), corporate editing increased from 2016 to 2021 and has decreased since then. There is a wide variety of companies involved in OSM, but the large number of edits and its concurrent decrease in edits is mainly driven by three companies, namely Meta, Kaart and Apple. Other researchers have investigated corporate mapping activity ​[1, 4, 7]​, but a decline in their mapping activity has not yet been reported or expected. The observed decline is particularly evident in the case of Apple, which experienced a peak in edits during 2020 (14 million edits) and 2021 (12 million edits) before decreasing by more than half in 2022 (4 million edits). - -Corporate edits are concentrated in high and medium HDI regions, with almost 80% of edits distributed across 32 countries. As seen in other analyses, non-organised mapping tends to focus on very high HDI regions ​[9]​, while humanitarian mapping tends to focus on low HDI regions [10]. The results presented here suggest that corporate mapping tends to focus more on high and medium HDI regions. The discussion about digital inequalities and power imbalances that may arise from corporate contributions in particular countries or regions should be ongoing, as it is a discussion for OSM as a whole. ​​​As of now, it is not clear why the large tech corporates map less. At the same time, it is unlikely that all high and medium HDI countries are completely mapped in OSM already [10]. - -Regarding the small-scale analysis our results show that there is no strong correlation between the increase or decrease in the mean corporate or non-corporate edits for the three selected countries. For most regions with a strong increase (high-high cluster) or decrease (low-low cluster) in corporate or non-corporate edits, there is no significant change for the other. This suggests that there is only a rather small influence of corporate mapping dynamics on other parts of the OSM mapping community in a country. - +Introduction: + +In recent years, with the emergence of corporate editing in OpenStreetMap (OSM), there has been interest, and in some cases concern, about its influence in OSM. For instance, large corporations like such as Apple, Microsoft, Meta and Amazon have hired large teams to edit in OSM ​[1]. The launch of the Overture Maps Foundation, by Amazon, Meta, Microsoft and TomTom hosted by the Linux Foundation in 2022 and the release of its first dataset [2] has also led to heated debates on the OSM forum, regarding the future of OSM. Concerns have been raised about the monopolisation of geodata, the replacement of OSM by other sites or the backlining of OSM [3]. + +Consequently, analysing and continuously monitoring the impact of corporate contributors and continuing to observe their fluctuating patterns of editing will be significant to the understanding of the sustainability of OSM. Therefore, this talk will look at corporate editing in OSM at three scales - global, national and local to answer the two research questions: + +(RQ1) What is the impact of corporate mapping on global scale mapping? + +(RQ2) What is the impact of corporate mapping on country and small-scale mapping? + +Methodology: + +There are two main avenues to track corporate contributors: Either through corporate affiliated OSM User IDs (UIDs) or through corporate hashtags in OSM changesets. UIDs of corporation affiliated mappers have been used in the past to track corporate activity in OSM (e.g. [1, 4, 5]). A list of affiliated usernames can be collected from disclosed lists on the OSM Wiki or corporations GitHub pages [6]. The second way to track corporate edits is through corporate hashtags in changesets. Since 2009, it became possible to add hashtags to changesets in OSM, and this has become common practice, especially to show affiliation to regions, events, organisations or corporations [7]. For the analysis presented here, in total 24 companies were tracked including Apple, Kaart, Amazon, Microsoft, TomTom, Grab, DigitalEgypt, Mapbox and Meta. We used tracking with hashtags was used as proposed by [7]. + +The dataset used for the analysis integrated data from two sources: The OpenStreetMap History Database [8] and the OSM Changeset database. The OSHDB was used to derive OSM geometries and attribute information as well as information about the editors. The data was then intersected with a dataset of country boundaries to assign a mapping to a specific country. The OSM changeset dataset was joined to this contribution dataset. The dataset included a plethora of information, but the most relevant columns for the analysis were the OSM ID, Changeset timestamp, hashtags and User IDs, country, year and month as well as the geometry information – including the centroids. (We aim at presenting this dataset in detail in another workshop at SOTM 2024.) + +At the global level, two analyses were carried out. First, the temporal development of corporate and total edits from 2016-01-01 – 2023-12-31, including a breakdown by individual corporation. Second, the absolute number of corporate edits per country and the percentage of corporate edits based on total edits per country for the period 2019-06-01 to 2023-05-31 were analyzed. For an additional overview, the country-level results were grouped by Human Development Index (HDI) class, for a more in depth understanding of the spatial distribution of corporate edits in respect to socio-economic factors. + +Countries with more than 15% corporate edits and more than 100,000 total edits in this period were selected for an in-depth analysis. A total of 28 countries met these requirements and we extracted the monthly corporate and non-corporate edits. The overall timeframe for analysis was divided into two time periods: t0 (2019-06-01– 2021-05-31) and t1 (2021-06-01 – 2023-05-31). For each country we derived the change in average activity for both corporate and non-corporate mapping. + +Three countries were selected from the 28 countries with high corporate mapping activity for the small-scale analysis: Colombia, Indonesia and the United Arab Emirates. For these countries we produced a high-resolution spatial dataset based on a H3 grid utilizing the centroid geometry of each OSM contribution. We performed a spatial auto-correlation analysis to identify regions where corporate (and non-corporate) edits have increased / declined over the past years. In addition to the maps, a normalized confusion matrix was calculated to compare the spatial autocorrelation results and present the overlap or difference between the trends in corporate and non-corporate mapping. + +Results and Discussion: + +At the global scale (RQ1), corporate editing increased from 2016 to 2021 and has decreased since then. There is a wide variety of companies involved in OSM, but the large number of edits and its concurrent decrease in edits is mainly driven by three companies, namely Meta, Kaart and Apple. Other researchers have investigated corporate mapping activity ​[1, 4, 7]​, but a decline in their mapping activity has not yet been reported or expected. The observed decline is particularly evident in the case of Apple, which experienced a peak in edits during 2020 (14 million edits) and 2021 (12 million edits) before decreasing by more than half in 2022 (4 million edits). + +Corporate edits are concentrated in high and medium HDI regions, with almost 80% of edits distributed across 32 countries. As seen in other analyses, non-organised mapping tends to focus on very high HDI regions ​[9]​, while humanitarian mapping tends to focus on low HDI regions [10]. The results presented here suggest that corporate mapping tends to focus more on high and medium HDI regions. The discussion about digital inequalities and power imbalances that may arise from corporate contributions in particular countries or regions should be ongoing, as it is a discussion for OSM as a whole. ​​​As of now, it is not clear why the large tech corporates map less. At the same time, it is unlikely that all high and medium HDI countries are completely mapped in OSM already [10]. + +Regarding the small-scale analysis our results show that there is no strong correlation between the increase or decrease in the mean corporate or non-corporate edits for the three selected countries. For most regions with a strong increase (high-high cluster) or decrease (low-low cluster) in corporate or non-corporate edits, there is no significant change for the other. This suggests that there is only a rather small influence of corporate mapping dynamics on other parts of the OSM mapping community in a country. + The ability to quantify the impact of corporate editing, particularly on volunteer mapping behaviour, continues to be an important measure for the OSM community. For example, further investigating would be necessary to understand the intentions and impacts of corporate mapping for various map features (not just looking at overall edit count). Understanding the intentions of different groups and communities in OSM and their impact on the data is a core necessity to obtain ’OSM Data Literacy’, especially for everyone who relies on high quality OSM data for research, business or decision making. diff --git a/sessions/LAZXYU.md b/sessions/LAZXYU.md index e2d6a50..5be71b4 100644 --- a/sessions/LAZXYU.md +++ b/sessions/LAZXYU.md @@ -1,4 +1,7 @@ --- +youtube: fW82AvpyXW0 +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50575-from-complexity-to-clarity-simplifying-openstreetmap-data-for-improved-active-transportation-analysis +recordings: [{'size': 125, 'length': 1624, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:59:54.256+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82010', 'event_url': 'https://api.media.ccc.de/public/events/cf5e318f-ec3f-5936-a5ae-cb9e2a76564f', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 60, 'length': 1624, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:43:46.026+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82007', 'event_url': 'https://api.media.ccc.de/public/events/cf5e318f-ec3f-5936-a5ae-cb9e2a76564f', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 41, 'length': 1624, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:31:55.719+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82002', 'event_url': 'https://api.media.ccc.de/public/events/cf5e318f-ec3f-5936-a5ae-cb9e2a76564f', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 24, 'length': 1624, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-27T19:29:02.680+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82001', 'event_url': 'https://api.media.ccc.de/public/events/cf5e318f-ec3f-5936-a5ae-cb9e2a76564f', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 105, 'length': 1624, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:17:57.800+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50575-eng-From_Complexity_to_Clarity_Simplifying_OpenStreetMap_Data_for_Improved_Active_Transportation_Analysis_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/81994', 'event_url': 'https://api.media.ccc.de/public/events/cf5e318f-ec3f-5936-a5ae-cb9e2a76564f', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "From Complexity to Clarity: Simplifying OpenStreetMap Data for Improved Active Transportation Analysis" code: "LAZXYU" @@ -16,31 +19,31 @@ OpenStreetMap (OSM) provides detailed street networks essential for analyzing ac
-Introduction -OpenStreetMap (OSM) offers comprehensive street networks that span nearly every city worldwide. The networks contain essential details like road type and name, and individual streets are often represented through multiple concurrent segments. The segments include separate lanes for motor vehicles, dedicated bike paths, and pedestrian walkways. -OSM's comprehensive dataset allows the creation of specialized networks customized for pedestrian and cyclist analysis, providing users with a powerful tool for understanding and improving active transportation (AT) infrastructure. These specialized networks play a pivotal role in monitoring and understanding walking and bicycling patterns, contributing to infrastructure enhancement aligned with cities' goals for fostering AT to combat traffic congestion, obesity, and air pollution (Nelson et al., 2021) -Nevertheless, the granularity of these networks may pose challenges in modeling AT users' movements on a street level. For example, when assessing AT safety or suggesting a walkability index at the street level, the current data representativeness on OSM necessitates significant manipulation to do so. Furthermore, owing to OSM's open-editing model, the standards for mapping elements are not consistently defined, leading to contentions and variations in data quality (Haklay, 2010). Individuals often map elements based on personal needs and knowledge, introducing inconsistencies in the dataset. Consequently, in some locales, all designated lanes for various users are meticulously mapped, while in others, only a single lane representing the presence of a street is depicted. Additionally, there are instances where only lanes for motor vehicles are detailed, with scant attention paid to lanes catering to other road user groups. -Previous research has endeavored to address this issue. For example, a study suggested a topology-preserving simplification of OSM network data for large-scale simulation in sumo (Meng et al., 2022). However, they primarily focus on less complex areas and prioritizing vehicular considerations when generating the new network over those of AT users. -Aim -In this study, we propose an innovative solution to generate an axial network specifically designed for monitoring and analyzing AT users, using exclusively OSM data. Our approach simplifies the network while preserving its topology. We apply this solution across diverse spatial contexts, from straightforward geographic regions to complex urban environments. Furthermore, we implement our methodology in several cities worldwide—Tel Aviv (Israel), Turin (Italy), and San Francisco (United State)—each characterized by unique urban structures and varying levels of economic development. - -Methodology -The preliminary tasks use OSMnx (Boeing, 2017) to acquire OSM street network data, converting it into a graph while correcting topological errors. Then, the data is stored in a geodata table, including polyline geometry, names, and road types. Our algorithm filters out unsuitable roads, like motorways and trunk roads, and replaces roundabouts with their central points. -The network is then ready for the multilane detection algorithm. Polylines identified in a multilane scenario are aggregated into a centerline and added to the Simplification OSM Data (SOD) network. Other polylines are added to the SOD network, retaining their original geometry. A multilane scenario is identified when polylines share the same street name, have similar angles, and are close together. Polylines are grouped by street name, and azimuth (0°-180°) narrows the angle range to ensure that parallel lines are considered parallel, regardless of orientation. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clusters similarly angled polylines using a 10° radius and a minimum of two samples. Outliers with significantly different angles are excluded. The remaining clusters apply a right-shifted buffer to each polyline. If two or more polylines in the same class overlap by at least 10% in the shifted buffer, they're classified as multilane, and the entire class is replaced with one or more centerlines. -The core idea behind creating a new centerline is to identify its start and end vertices and then add intermediate vertices to preserve the overall shape of multilane polylines. Overlapping buffers are merged into a single polygon, and the two polygon vertices that best define the original polylines are used to establish the new centerline's start and end. Intermediate vertices are then added at regular intervals to maintain the original polylines' orientation. -The simplification process introduces significant changes to the locations of many polylines, resulting in issues of continuity, topology, accuracy, and inconsistency in the SOD network. Most problems can be resolved using existing methods, but connecting roundabouts requires extra effort. This process has three steps: transforming the roundabout representation to a point, connecting nearby dead-end polylines, and linking polylines in proximity. Following these steps ensures proper continuity and maintains the network's topology. - -Findings -The case study centered on Turin, Italy, simplified its street network to 11,807 polylines from an initial 49,750. This effort reduced the complexity of 411 streets, converting 138 roundabouts to single points. Despite some challenges near intersections, the final version preserved topology. -For validation, 43 streets in Turin were reviewed, revealing a 51% success rate, 28% with minor flaws, and 14% with partial success. Issues such as threshold errors, external mapping inaccuracies, and ambiguous street configurations affected the results. Similar challenges were faced in Tel Aviv, Israel, where 50% of 22 test streets matched perfectly with the reference network. Yet, 23% had minor issues, and 9% were entirely incorrect. In San Francisco, the comparison showed 80% accuracy with 20 streets evaluated. While most streets were correctly simplified, minor flaws were present in a few cases, mainly due to inconsistencies between the SOD and reference networks. Overall, the methodology successfully streamlined street networks, although it achieved varying rates of success across different cities. - -Discussion -Our study offers a robust methodology for generating axial networks for AT users using OSM data, balancing data simplification with topology preservation. Its successful application across diverse cities such as Turin, Tel Aviv, and San Francisco demonstrate its versatility and effectiveness in varied urban environments. The approach simplifies the complex urban network data, streamlining pedestrian and bicycle analysis while retaining essential details. This enables urban planners and policymakers to better monitor and understand AT patterns, leading to infrastructure improvements that support safer, more efficient, and environmentally friendly urban mobility. -Our research offers both scientific contributions and practical benefits. Scientifically, it has been applied to evaluate the built environment for pedestrian walkability using a spatial data clustering approach. Additionally, it has been utilized in research to evaluate safety and bike network connectivity, aiming to improve bicycle and pedestrian infrastructure in California cities. Practically, this work has been published on GitHub, making the code accessible to everyone for their specific needs and goals. - -References -Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139. -Haklay, M. (2010). How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning B: Planning and Design, 37(4), 682–703. -Meng, Z., Du, X., Sottovia, P., Foroni, D., Axenie, C., Wieder, A., Eckhoff, D., Bortoli, S., Knoll, A., & Sommer, C. (2022). Topology-Preserving Simplification of OpenStreetMap Network Data for Large-scale Simulation in SUMO. SUMO Conference Proceedings, 3, 181–197. +Introduction +OpenStreetMap (OSM) offers comprehensive street networks that span nearly every city worldwide. The networks contain essential details like road type and name, and individual streets are often represented through multiple concurrent segments. The segments include separate lanes for motor vehicles, dedicated bike paths, and pedestrian walkways. +OSM's comprehensive dataset allows the creation of specialized networks customized for pedestrian and cyclist analysis, providing users with a powerful tool for understanding and improving active transportation (AT) infrastructure. These specialized networks play a pivotal role in monitoring and understanding walking and bicycling patterns, contributing to infrastructure enhancement aligned with cities' goals for fostering AT to combat traffic congestion, obesity, and air pollution (Nelson et al., 2021) +Nevertheless, the granularity of these networks may pose challenges in modeling AT users' movements on a street level. For example, when assessing AT safety or suggesting a walkability index at the street level, the current data representativeness on OSM necessitates significant manipulation to do so. Furthermore, owing to OSM's open-editing model, the standards for mapping elements are not consistently defined, leading to contentions and variations in data quality (Haklay, 2010). Individuals often map elements based on personal needs and knowledge, introducing inconsistencies in the dataset. Consequently, in some locales, all designated lanes for various users are meticulously mapped, while in others, only a single lane representing the presence of a street is depicted. Additionally, there are instances where only lanes for motor vehicles are detailed, with scant attention paid to lanes catering to other road user groups. +Previous research has endeavored to address this issue. For example, a study suggested a topology-preserving simplification of OSM network data for large-scale simulation in sumo (Meng et al., 2022). However, they primarily focus on less complex areas and prioritizing vehicular considerations when generating the new network over those of AT users. +Aim +In this study, we propose an innovative solution to generate an axial network specifically designed for monitoring and analyzing AT users, using exclusively OSM data. Our approach simplifies the network while preserving its topology. We apply this solution across diverse spatial contexts, from straightforward geographic regions to complex urban environments. Furthermore, we implement our methodology in several cities worldwide—Tel Aviv (Israel), Turin (Italy), and San Francisco (United State)—each characterized by unique urban structures and varying levels of economic development. + +Methodology +The preliminary tasks use OSMnx (Boeing, 2017) to acquire OSM street network data, converting it into a graph while correcting topological errors. Then, the data is stored in a geodata table, including polyline geometry, names, and road types. Our algorithm filters out unsuitable roads, like motorways and trunk roads, and replaces roundabouts with their central points. +The network is then ready for the multilane detection algorithm. Polylines identified in a multilane scenario are aggregated into a centerline and added to the Simplification OSM Data (SOD) network. Other polylines are added to the SOD network, retaining their original geometry. A multilane scenario is identified when polylines share the same street name, have similar angles, and are close together. Polylines are grouped by street name, and azimuth (0°-180°) narrows the angle range to ensure that parallel lines are considered parallel, regardless of orientation. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clusters similarly angled polylines using a 10° radius and a minimum of two samples. Outliers with significantly different angles are excluded. The remaining clusters apply a right-shifted buffer to each polyline. If two or more polylines in the same class overlap by at least 10% in the shifted buffer, they're classified as multilane, and the entire class is replaced with one or more centerlines. +The core idea behind creating a new centerline is to identify its start and end vertices and then add intermediate vertices to preserve the overall shape of multilane polylines. Overlapping buffers are merged into a single polygon, and the two polygon vertices that best define the original polylines are used to establish the new centerline's start and end. Intermediate vertices are then added at regular intervals to maintain the original polylines' orientation. +The simplification process introduces significant changes to the locations of many polylines, resulting in issues of continuity, topology, accuracy, and inconsistency in the SOD network. Most problems can be resolved using existing methods, but connecting roundabouts requires extra effort. This process has three steps: transforming the roundabout representation to a point, connecting nearby dead-end polylines, and linking polylines in proximity. Following these steps ensures proper continuity and maintains the network's topology. + +Findings +The case study centered on Turin, Italy, simplified its street network to 11,807 polylines from an initial 49,750. This effort reduced the complexity of 411 streets, converting 138 roundabouts to single points. Despite some challenges near intersections, the final version preserved topology. +For validation, 43 streets in Turin were reviewed, revealing a 51% success rate, 28% with minor flaws, and 14% with partial success. Issues such as threshold errors, external mapping inaccuracies, and ambiguous street configurations affected the results. Similar challenges were faced in Tel Aviv, Israel, where 50% of 22 test streets matched perfectly with the reference network. Yet, 23% had minor issues, and 9% were entirely incorrect. In San Francisco, the comparison showed 80% accuracy with 20 streets evaluated. While most streets were correctly simplified, minor flaws were present in a few cases, mainly due to inconsistencies between the SOD and reference networks. Overall, the methodology successfully streamlined street networks, although it achieved varying rates of success across different cities. + +Discussion +Our study offers a robust methodology for generating axial networks for AT users using OSM data, balancing data simplification with topology preservation. Its successful application across diverse cities such as Turin, Tel Aviv, and San Francisco demonstrate its versatility and effectiveness in varied urban environments. The approach simplifies the complex urban network data, streamlining pedestrian and bicycle analysis while retaining essential details. This enables urban planners and policymakers to better monitor and understand AT patterns, leading to infrastructure improvements that support safer, more efficient, and environmentally friendly urban mobility. +Our research offers both scientific contributions and practical benefits. Scientifically, it has been applied to evaluate the built environment for pedestrian walkability using a spatial data clustering approach. Additionally, it has been utilized in research to evaluate safety and bike network connectivity, aiming to improve bicycle and pedestrian infrastructure in California cities. Practically, this work has been published on GitHub, making the code accessible to everyone for their specific needs and goals. + +References +Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139. +Haklay, M. (2010). How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning B: Planning and Design, 37(4), 682–703. +Meng, Z., Du, X., Sottovia, P., Foroni, D., Axenie, C., Wieder, A., Eckhoff, D., Bortoli, S., Knoll, A., & Sommer, C. (2022). Topology-Preserving Simplification of OpenStreetMap Network Data for Large-scale Simulation in SUMO. SUMO Conference Proceedings, 3, 181–197. Nelson, T., Ferster, C., Laberee, K., Fuller, D., & Winters, M. (2021). Crowdsourced data for bicycling research and practice. Transport Reviews, 41(1), 97–114. diff --git a/sessions/MKPJFW.md b/sessions/MKPJFW.md index 9348fa9..c1d42bd 100644 --- a/sessions/MKPJFW.md +++ b/sessions/MKPJFW.md @@ -1,4 +1,6 @@ --- +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50539-analysis-of-renewable-energy-infrastructure-representations-in-openstreetmap +recordings: [{'size': 41, 'length': 574, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T20:32:40.468+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82015', 'event_url': 'https://api.media.ccc.de/public/events/13edf2b1-4371-55cc-b733-a199dcb45ca5', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 20, 'length': 574, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:26:55.356+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82014', 'event_url': 'https://api.media.ccc.de/public/events/13edf2b1-4371-55cc-b733-a199dcb45ca5', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 8, 'length': 574, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-28T20:20:58.677+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82013', 'event_url': 'https://api.media.ccc.de/public/events/13edf2b1-4371-55cc-b733-a199dcb45ca5', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 13, 'length': 574, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:20:55.169+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82012', 'event_url': 'https://api.media.ccc.de/public/events/13edf2b1-4371-55cc-b733-a199dcb45ca5', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 26, 'length': 574, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T20:18:39.917+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50539-eng-Analysis_of_renewable_energy_infrastructure_representations_in_OpenStreetMap_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82011', 'event_url': 'https://api.media.ccc.de/public/events/13edf2b1-4371-55cc-b733-a199dcb45ca5', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Analysis of renewable energy infrastructure representations in OpenStreetMap" code: "MKPJFW" @@ -16,27 +18,27 @@ The research evaluates the accuracy and completeness of wind and solar energy in
-We are witnessing the rise of a collective awareness of the importance of building a more environmentally sustainable future. Within this context, the relevance of renewable energy sources is widely acknowledged; however, to support the energy transition, the availability of reliable data about energy supply, infrastructures, and their environmental impacts is essential [1]. OpenStreetMap (OSM) emerges as a valuable data source to meet these requirements. In this work, we describe our research on evaluating the OSM database in a study of wind and solar energy infrastructures. As a case-study, we analyse two countries: Belgium and Ireland. - -Data within OSM is well-known to have a diverse level of completeness and granularity [2]. Considering OSM's vibrant mapping communities coupled with both (a) the environmental visibility of wind and solar energy infrastructures and (b) their relatively limited number compared to other built infrastructures, it is reasonable to assume that the majority of these installations are well mapped within OSM. OSM energy-related objects are mapped under the _“power”_ tag, with available key-value combinations to identify wind and solar sources. Wind turbines are commonly tagged as _“power=generator”_ and _“generator:source=wind”_, while solar farms are identified as _“power=plant”_ and _“plant:source=solar”_. - -By combining OSM data with the CORINE Land Cover (CLC) inventory we considers two research questions. Firstly, we seek to identify common mapping errors and tagging issues associated with wind and solar energy infrastructure representation within OSM. This involves examining geometries and tagging mistakes while evaluating the accuracy and completeness of these infrastructures. Secondly, we perform a geographical analysis to consider the distribution of infrastructures across various CLC land covers. We seek to detect patterns around land cover and renewable energy infrastructure. Our methodology is summarised as follows: OSM data, in PBF format, is downloaded from _GeoFabrik_. Initially here we just consider Ireland and Belgium due to local knowledge and their manageable data sizes. Analysis is performed using _Python_ and the _osmium_ library. Pending acceptance, source code will be made openly available on GitHub in documented Jupyter notebooks. -We answer our research questions using three key steps: -1. Assess available wind and solar infrastructures in OSM for the correctness of OSM datatypes and potential geometric errors. -2. Differentiate between individual installations and larger "farms", to evaluate the quality and completeness of OSM data. -3. Investigate commonalities around land use surrounding renewable energy infrastructures using CLC. - -Initially, we extract all OSM objects with _“power”_ tag =_“plant”_ or _“generator”_, yielding a full listing of all available power sources. We filter solar and wind sources based on the _"generator:source"_ or _"plant:source"_ tags. The accuracy of the OSM datatypes and geometries is checked before moving to "farms" identification. To accurately differentiate single installations from farms, we analyze solar and wind sources separately due to their different geometric nature. - -We employ a point-in-polygon search with spatial indexes to assign nodes – of either wind or solar type – to intersecting areas of the same energy type. This process raises some geometric questions concerning the meaning of areas without nodes and nodes not linked to any area. We observed several issues: (a) not mapping individual panels within solar farms or defining turbines as circular areas, (b) nodes not associated with any area, (c) unlinked solar nodes representing private installations, (d) the absence of OSM areas or relations for turbines frequently indicated incomplete mapping. This final issue is significant: 91.4% of wind nodes in Belgium and around 87.4% in Ireland are not located within any mapped area. Considering the limited number of turbines included in OSM areas or relations, we employed spatial clustering on all turbines to identify wind farms and validate our findings by automatically comparing clusters with existing OSM areas and relations. - -DBSCAN (Density-based spatial clustering of applications with noise) is particularly suited for our purpose. One of the most important DBSCAN parameters is the maximum distance between two samples belonging to the same cluster which we set as 5 times the rotor diameter [3]. We assume a diameter value of 130 meters for all turbines [3] considering the frequent absence of the _"rotor:diameter"_ tag. Comparing clustering results with OSM data allows us to evaluate quality and completeness of areas and relations, to identify new farms, and to extend existing linkages to unassigned infrastructures. - -Due to their geometric nature, the process described cannot be applied to solar infrastructures. Given that all remaining solar data are areas, our methodology proposes two different processes, based on the power-tag value (“generator” or “plant”). Although OSM guidelines suggest that solar farms should be tagged as “plant”, deviations from this standard are possible. To avoid discarding valid data, we conducted an area-in-area search on solar generators. This approach assumes that if a solar generator area encompasses multiple solar generators, it may denote a farm. This process enables us to identify a few tagging mistakes where the _"generator"_ value was used instead of _"plant"_. While it may be possible to apply the same approach on solar _"plant"_, this would cause a significant data loss, thus we opt for keeping all plant-objects. Ultimately, this decision is strongly dependent on the data accuracy requirements. The refined datasets provide a comprehensive overview of wind and solar energy sources, facilitating further analyses into renewable energy. - -Our second research question considerations the analysis of land uses around energy infrastructure by integrating CLC. We use an arbitrary buffer of 1000m for this analysis. In Belgium, around 18% of wind farms are located within 1000 meters from heterogeneous agricultural areas, while 17% and 15% are near urban fabric and arable land respectively. In Ireland, most wind farms are near pastures (~24%), scrub (~18%) and forests (~18%). We notice how agricultural areas, in the form of heterogeneous agricultural areas, pastures, or arable land seem to prevail in both contexts. For wind energy, artificial surfaces appear relevant only in Belgium; however, both countries have solar farms near urban fabrics LC. Within the buffer from solar infrastructures this LC appears ~19% of the time in Belgium and ~12% in Ireland. In Belgium, heterogeneous agricultural areas (~19%) and forests (~12%) are also significant, while pastures predominate in Ireland (~31%), followed by arable land (~16%). However, 56% of the Irish territory is classified as pasture LC. - -Our work seeks to assess and improve completeness and accuracy of renewable energy infrastructure data in OSM. Our analysis distinguishes between individual installations and larger farms. Our strategy based on density-based clustering for identifying wind farms faciliates evaluation of the OSM data. We developed methods to associate solar panels to farms thereby mitigating tagging errors. Overall, we highlight challenges arising from inconsistent mapping practices and deviation from OSM mapping guidelines. The refined datasets offer comprehensive insights into wind and solar energy sources allowing additional analyses and assessment of their integration into the surrounding landscape. - +We are witnessing the rise of a collective awareness of the importance of building a more environmentally sustainable future. Within this context, the relevance of renewable energy sources is widely acknowledged; however, to support the energy transition, the availability of reliable data about energy supply, infrastructures, and their environmental impacts is essential [1]. OpenStreetMap (OSM) emerges as a valuable data source to meet these requirements. In this work, we describe our research on evaluating the OSM database in a study of wind and solar energy infrastructures. As a case-study, we analyse two countries: Belgium and Ireland. + +Data within OSM is well-known to have a diverse level of completeness and granularity [2]. Considering OSM's vibrant mapping communities coupled with both (a) the environmental visibility of wind and solar energy infrastructures and (b) their relatively limited number compared to other built infrastructures, it is reasonable to assume that the majority of these installations are well mapped within OSM. OSM energy-related objects are mapped under the _“power”_ tag, with available key-value combinations to identify wind and solar sources. Wind turbines are commonly tagged as _“power=generator”_ and _“generator:source=wind”_, while solar farms are identified as _“power=plant”_ and _“plant:source=solar”_. + +By combining OSM data with the CORINE Land Cover (CLC) inventory we considers two research questions. Firstly, we seek to identify common mapping errors and tagging issues associated with wind and solar energy infrastructure representation within OSM. This involves examining geometries and tagging mistakes while evaluating the accuracy and completeness of these infrastructures. Secondly, we perform a geographical analysis to consider the distribution of infrastructures across various CLC land covers. We seek to detect patterns around land cover and renewable energy infrastructure. Our methodology is summarised as follows: OSM data, in PBF format, is downloaded from _GeoFabrik_. Initially here we just consider Ireland and Belgium due to local knowledge and their manageable data sizes. Analysis is performed using _Python_ and the _osmium_ library. Pending acceptance, source code will be made openly available on GitHub in documented Jupyter notebooks. +We answer our research questions using three key steps: +1. Assess available wind and solar infrastructures in OSM for the correctness of OSM datatypes and potential geometric errors. +2. Differentiate between individual installations and larger "farms", to evaluate the quality and completeness of OSM data. +3. Investigate commonalities around land use surrounding renewable energy infrastructures using CLC. + +Initially, we extract all OSM objects with _“power”_ tag =_“plant”_ or _“generator”_, yielding a full listing of all available power sources. We filter solar and wind sources based on the _"generator:source"_ or _"plant:source"_ tags. The accuracy of the OSM datatypes and geometries is checked before moving to "farms" identification. To accurately differentiate single installations from farms, we analyze solar and wind sources separately due to their different geometric nature. + +We employ a point-in-polygon search with spatial indexes to assign nodes – of either wind or solar type – to intersecting areas of the same energy type. This process raises some geometric questions concerning the meaning of areas without nodes and nodes not linked to any area. We observed several issues: (a) not mapping individual panels within solar farms or defining turbines as circular areas, (b) nodes not associated with any area, (c) unlinked solar nodes representing private installations, (d) the absence of OSM areas or relations for turbines frequently indicated incomplete mapping. This final issue is significant: 91.4% of wind nodes in Belgium and around 87.4% in Ireland are not located within any mapped area. Considering the limited number of turbines included in OSM areas or relations, we employed spatial clustering on all turbines to identify wind farms and validate our findings by automatically comparing clusters with existing OSM areas and relations. + +DBSCAN (Density-based spatial clustering of applications with noise) is particularly suited for our purpose. One of the most important DBSCAN parameters is the maximum distance between two samples belonging to the same cluster which we set as 5 times the rotor diameter [3]. We assume a diameter value of 130 meters for all turbines [3] considering the frequent absence of the _"rotor:diameter"_ tag. Comparing clustering results with OSM data allows us to evaluate quality and completeness of areas and relations, to identify new farms, and to extend existing linkages to unassigned infrastructures. + +Due to their geometric nature, the process described cannot be applied to solar infrastructures. Given that all remaining solar data are areas, our methodology proposes two different processes, based on the power-tag value (“generator” or “plant”). Although OSM guidelines suggest that solar farms should be tagged as “plant”, deviations from this standard are possible. To avoid discarding valid data, we conducted an area-in-area search on solar generators. This approach assumes that if a solar generator area encompasses multiple solar generators, it may denote a farm. This process enables us to identify a few tagging mistakes where the _"generator"_ value was used instead of _"plant"_. While it may be possible to apply the same approach on solar _"plant"_, this would cause a significant data loss, thus we opt for keeping all plant-objects. Ultimately, this decision is strongly dependent on the data accuracy requirements. The refined datasets provide a comprehensive overview of wind and solar energy sources, facilitating further analyses into renewable energy. + +Our second research question considerations the analysis of land uses around energy infrastructure by integrating CLC. We use an arbitrary buffer of 1000m for this analysis. In Belgium, around 18% of wind farms are located within 1000 meters from heterogeneous agricultural areas, while 17% and 15% are near urban fabric and arable land respectively. In Ireland, most wind farms are near pastures (~24%), scrub (~18%) and forests (~18%). We notice how agricultural areas, in the form of heterogeneous agricultural areas, pastures, or arable land seem to prevail in both contexts. For wind energy, artificial surfaces appear relevant only in Belgium; however, both countries have solar farms near urban fabrics LC. Within the buffer from solar infrastructures this LC appears ~19% of the time in Belgium and ~12% in Ireland. In Belgium, heterogeneous agricultural areas (~19%) and forests (~12%) are also significant, while pastures predominate in Ireland (~31%), followed by arable land (~16%). However, 56% of the Irish territory is classified as pasture LC. + +Our work seeks to assess and improve completeness and accuracy of renewable energy infrastructure data in OSM. Our analysis distinguishes between individual installations and larger farms. Our strategy based on density-based clustering for identifying wind farms faciliates evaluation of the OSM data. We developed methods to associate solar panels to farms thereby mitigating tagging errors. Overall, we highlight challenges arising from inconsistent mapping practices and deviation from OSM mapping guidelines. The refined datasets offer comprehensive insights into wind and solar energy sources allowing additional analyses and assessment of their integration into the surrounding landscape. + The next steps for this work include validating our approach for a larger set of countries and regions while also integrating further internal and external completeness and quality evaluations. diff --git a/sessions/NQHRLV.md b/sessions/NQHRLV.md index 82dc7d1..a9e8ad6 100644 --- a/sessions/NQHRLV.md +++ b/sessions/NQHRLV.md @@ -1,4 +1,6 @@ --- +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-48682-crisis-mapping-teaching-high-school-ell-students-how-to-make-maps-that-save-lives +recordings: [{'size': 64, 'length': 807, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T21:12:22.565+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82029', 'event_url': 'https://api.media.ccc.de/public/events/5308911c-ffb1-53d5-8e7f-cbd088f01acb', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 30, 'length': 807, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T21:00:55.306+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82027', 'event_url': 'https://api.media.ccc.de/public/events/5308911c-ffb1-53d5-8e7f-cbd088f01acb', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 12, 'length': 807, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-28T20:55:59.620+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82026', 'event_url': 'https://api.media.ccc.de/public/events/5308911c-ffb1-53d5-8e7f-cbd088f01acb', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 21, 'length': 807, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:51:46.423+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82024', 'event_url': 'https://api.media.ccc.de/public/events/5308911c-ffb1-53d5-8e7f-cbd088f01acb', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 54, 'length': 807, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T20:39:18.403+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-48682-eng-Crisis_Mapping_Teaching_High_School_ELL_Students_How_to_Make_Maps_That_Save_Lives_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82019', 'event_url': 'https://api.media.ccc.de/public/events/5308911c-ffb1-53d5-8e7f-cbd088f01acb', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Crisis Mapping: Teaching High School ELL Students How to Make Maps That Save Lives" code: "NQHRLV" @@ -16,30 +18,30 @@ This paper presents the learning outcomes of a Mini-Mapathon course developed, i
-. I designed and developed the Mini-Mapathon curriculum to answer three key research questions below. - -1. How did the design support changes in students’ perceptions of their crisis mapping knowledge and skills? -2. How did participating in the Mini-Mapathon support student expressed interest in crisis mapping in the future? -3. How did the Mini-Mapathon support students in engaging crisis mapping? - -I designed and delivered the Mini-Mapathon, via three 45-minute Human Geography courses to 28 junior Asian high school students at an international school in Beijing, China. The English Language Learners (ELL) student population were all Chinese and their ages ranged from 16-18, consisting of 15 male students and 13 female students. Prior to implementing the research project with 28 Human Geography students, I researched the best way to teach crisis mapping to ELL students by participating in Mapathons and Mapalongs. I piloted three crisis mapping Mini-Mapathons for 55 Asian 4th grade students in three classrooms after learning crisis mapping was done effectively with 10 year old students in Milan, Italy (Gaspari, et al., 2021). The pilot programs with 4th grade Asian students and subsequent project were implemented only after the 4th grade students learned about crises in their IB-PYP curriculum, and after I conducted an extensive literature review of this relatively new (2005), interdisciplinary and innovative field of crisis mapping, investigated many mapping software platforms, and spoke to representatives from www.ushahidi.org, www.hotosm.org , and www.missingmaps.com. -A website was built (www.crisismapping.weebly.com) to turn the Mini-Mapathon experience into an exportable educational activity that could be replicated or delivered in formal and informal learning environments. -Using the ADDIE approach, I sought to design, implement, and evaluate a Mini-Mapathon curriculum to answer my three research questions. I implemented my applied research project on teaching crisis mapping through a Mini-Mapathon and collected pre and post surveys in late April, 2022, during the spring semester at an international high school in my three Human Geography classes. Twenty-eight Asian students participated in the Mini-Mapathon so that medicine and services could be delivered to vulnerable populations in Nigeria and Zimbabwe by Doctors Without Borders and The Red Cross. During the 45 minute Mini-Mapathons, students were taught how to map buildings and roads using Humanitarian Open Street Mapping software via www.hotosm.org and they took pre and post surveys so that I could better understand and measure how students learn during Mapathons and determine if my methodology for teaching crisis mapping was effective (Branch, 2009). -The learning objectives of the Mini-Mapathon design were as follows: -1) Students will be able to co-create interactive open street maps using geo-spatial software. -2) Students will be able to analyze the role maps play in crisis response such as refugee crises and disasters and identify the stakeholders including citizens, international humanitarian organizations such as UNHCR, Doctors Without Borders, and Red Cross, NGO’s, government agencies, and military branches. -3) Students will be able to develop geographical knowledge and spatial awareness. -I delivered pre and post surveys to better understand how students learn, what they learn, and assess the quality of crisis mapping instruction in my three Human Geography courses with 28 Asian high school students. How to Create an Account tutorial along with the other static and video tutorials can now be found on the website I built www.crisismapping.weebly.com. -I began each class with a 2–3-minute video focusing on the problem, population in need and showcasing the work of the Spanish Red Cross, UNHCR, or Doctors Without Borders, to increase cultural and historical context and show the organization who can operationalize our map to provide relief to those in need. I then proceeded to explain that some places do not have accurate maps because they do not have Google cars driving around or adequate resources in the government to make up to date maps, however, volunteers like us can make the new maps together using satellite imagery. I asked the students to create their own OSM accounts in previous classes because we had been using the OpenStreetMap resource to explore chokepoints, or straights and canals, to better understand geography and global trade in previous lessons. I provided anonymous usernames and passwords if students had not yet created their OSM accounts to save time. Some opted to use the Tutorial How to Create An OSM Account and some students taught others how to create an account quickly. - -Next, I proceeded to implement the following step by step in class instructions in order to make learning visible and meet the academic language needs of the ELL students (Hattie, 2008; Yoder, et al., 2016). -Step 1) Watch a fellow student map in front of the classroom following the teacher instruction through a four-step tutorial How To Map A Building. The tutorial can be found on www.crisismapping.weebly.com -Step 2) Review the four-step process by coaching the student verbally through the four-step tutorial How to Map a Building. -Step 3) Correct the teacher’s mistakes of not following the order and incorrectly mapping the building size, and mapping a shadow. -Step 4) Answer any questions students may have. -Step 5) Ask students to start mapping their first building and raise their hands before saving and uploading their work so the teacher or aid can inspect and correct their work if needed. - -PDF and video tutorials on How to Map a Building and How to Map a Road were delivered through the school’s information communication technology platform so students could learn at their own pace through multi-modal scaffolded instruction. -The population sample of 28 Asian ELL high school junior students completed pre-surveys prior to the learning intervention or Mapathon and then completed the post survey. The pre and post survey questions were a mix of qualitative and quantitative questions (see Table 3). The quantitative survey data was analyzed using Microsoft Excel. The descriptive analysis was performed with SPSS to find the frequencies, percentages, the mean and standard deviation of survey question data. The descriptive statistics are presented below in the form of tables, graphs, and charts below. +. I designed and developed the Mini-Mapathon curriculum to answer three key research questions below. + +1. How did the design support changes in students’ perceptions of their crisis mapping knowledge and skills? +2. How did participating in the Mini-Mapathon support student expressed interest in crisis mapping in the future? +3. How did the Mini-Mapathon support students in engaging crisis mapping? + +I designed and delivered the Mini-Mapathon, via three 45-minute Human Geography courses to 28 junior Asian high school students at an international school in Beijing, China. The English Language Learners (ELL) student population were all Chinese and their ages ranged from 16-18, consisting of 15 male students and 13 female students. Prior to implementing the research project with 28 Human Geography students, I researched the best way to teach crisis mapping to ELL students by participating in Mapathons and Mapalongs. I piloted three crisis mapping Mini-Mapathons for 55 Asian 4th grade students in three classrooms after learning crisis mapping was done effectively with 10 year old students in Milan, Italy (Gaspari, et al., 2021). The pilot programs with 4th grade Asian students and subsequent project were implemented only after the 4th grade students learned about crises in their IB-PYP curriculum, and after I conducted an extensive literature review of this relatively new (2005), interdisciplinary and innovative field of crisis mapping, investigated many mapping software platforms, and spoke to representatives from www.ushahidi.org, www.hotosm.org , and www.missingmaps.com. +A website was built (www.crisismapping.weebly.com) to turn the Mini-Mapathon experience into an exportable educational activity that could be replicated or delivered in formal and informal learning environments. +Using the ADDIE approach, I sought to design, implement, and evaluate a Mini-Mapathon curriculum to answer my three research questions. I implemented my applied research project on teaching crisis mapping through a Mini-Mapathon and collected pre and post surveys in late April, 2022, during the spring semester at an international high school in my three Human Geography classes. Twenty-eight Asian students participated in the Mini-Mapathon so that medicine and services could be delivered to vulnerable populations in Nigeria and Zimbabwe by Doctors Without Borders and The Red Cross. During the 45 minute Mini-Mapathons, students were taught how to map buildings and roads using Humanitarian Open Street Mapping software via www.hotosm.org and they took pre and post surveys so that I could better understand and measure how students learn during Mapathons and determine if my methodology for teaching crisis mapping was effective (Branch, 2009). +The learning objectives of the Mini-Mapathon design were as follows: +1) Students will be able to co-create interactive open street maps using geo-spatial software. +2) Students will be able to analyze the role maps play in crisis response such as refugee crises and disasters and identify the stakeholders including citizens, international humanitarian organizations such as UNHCR, Doctors Without Borders, and Red Cross, NGO’s, government agencies, and military branches. +3) Students will be able to develop geographical knowledge and spatial awareness. +I delivered pre and post surveys to better understand how students learn, what they learn, and assess the quality of crisis mapping instruction in my three Human Geography courses with 28 Asian high school students. How to Create an Account tutorial along with the other static and video tutorials can now be found on the website I built www.crisismapping.weebly.com. +I began each class with a 2–3-minute video focusing on the problem, population in need and showcasing the work of the Spanish Red Cross, UNHCR, or Doctors Without Borders, to increase cultural and historical context and show the organization who can operationalize our map to provide relief to those in need. I then proceeded to explain that some places do not have accurate maps because they do not have Google cars driving around or adequate resources in the government to make up to date maps, however, volunteers like us can make the new maps together using satellite imagery. I asked the students to create their own OSM accounts in previous classes because we had been using the OpenStreetMap resource to explore chokepoints, or straights and canals, to better understand geography and global trade in previous lessons. I provided anonymous usernames and passwords if students had not yet created their OSM accounts to save time. Some opted to use the Tutorial How to Create An OSM Account and some students taught others how to create an account quickly. + +Next, I proceeded to implement the following step by step in class instructions in order to make learning visible and meet the academic language needs of the ELL students (Hattie, 2008; Yoder, et al., 2016). +Step 1) Watch a fellow student map in front of the classroom following the teacher instruction through a four-step tutorial How To Map A Building. The tutorial can be found on www.crisismapping.weebly.com +Step 2) Review the four-step process by coaching the student verbally through the four-step tutorial How to Map a Building. +Step 3) Correct the teacher’s mistakes of not following the order and incorrectly mapping the building size, and mapping a shadow. +Step 4) Answer any questions students may have. +Step 5) Ask students to start mapping their first building and raise their hands before saving and uploading their work so the teacher or aid can inspect and correct their work if needed. + +PDF and video tutorials on How to Map a Building and How to Map a Road were delivered through the school’s information communication technology platform so students could learn at their own pace through multi-modal scaffolded instruction. +The population sample of 28 Asian ELL high school junior students completed pre-surveys prior to the learning intervention or Mapathon and then completed the post survey. The pre and post survey questions were a mix of qualitative and quantitative questions (see Table 3). The quantitative survey data was analyzed using Microsoft Excel. The descriptive analysis was performed with SPSS to find the frequencies, percentages, the mean and standard deviation of survey question data. The descriptive statistics are presented below in the form of tables, graphs, and charts below. I used descriptive statistics and analysis instead of inferential statistics because this was a pilot project with a small sample size. The goal was to understand the impact of the new curriculum on this particular population and not to generalize effects of an intervention for all similar students. diff --git a/sessions/PG3K3G.md b/sessions/PG3K3G.md index efd20c4..e37dd3e 100644 --- a/sessions/PG3K3G.md +++ b/sessions/PG3K3G.md @@ -1,4 +1,7 @@ --- +youtube: _EnasIauBsg +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50240-assessing-the-performance-of-ai-assisted-mapping-of-building-footprints-for-osm +recordings: [{'size': 95, 'length': 1294, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:41:28.568+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82003', 'event_url': 'https://api.media.ccc.de/public/events/b6d81c8d-70a8-5d69-9af0-a507e6b0f642', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 46, 'length': 1294, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:28:11.315+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/81999', 'event_url': 'https://api.media.ccc.de/public/events/b6d81c8d-70a8-5d69-9af0-a507e6b0f642', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 33, 'length': 1294, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:18:12.952+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/81995', 'event_url': 'https://api.media.ccc.de/public/events/b6d81c8d-70a8-5d69-9af0-a507e6b0f642', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 19, 'length': 1294, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-27T19:15:57.145+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/81993', 'event_url': 'https://api.media.ccc.de/public/events/b6d81c8d-70a8-5d69-9af0-a507e6b0f642', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 83, 'length': 1294, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:13:46.994+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50240-eng-Assessing_the_performance_of_AI-assisted_mapping_of_building_footprints_for_OSM_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/81991', 'event_url': 'https://api.media.ccc.de/public/events/b6d81c8d-70a8-5d69-9af0-a507e6b0f642', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Assessing the performance of AI-assisted mapping of building footprints for OSM" code: "PG3K3G" @@ -16,27 +19,27 @@ fAIr is an open AI-assisted mapping service developed by the Humanitarian OpenSt
-**Introduction** -Building footprints features are useful in a wide range of applications such as disaster assessment, urban planning, and environmental monitoring (You et al., 2018; Owusu et al., 2021; Yang, Matsushita, & Zhang, 2023), and their identification has been gaining increasing interest and attention from the ML research for Earth Observation (Hoeser, Bachofer, & Kuenzer, 2020). Particularly in the disaster response context, accurate and prompt availability of such information is crucial (Boccardo & Giulio Tonolo, 2015; Deng, 2022; Sun et al., 2022). -fAIr, developed by the Humanitarian OpenStreetMap Team (HOT), a fully open AI-assisted mapping service to generate semi-automated building footprints features, addresses this need (fAIr website, 2022). fAIr stands for “Free and open source AI that is resilient for local contexts, and represents the Responsibility of HOT for local communities and humanitarian mapping", reflecting the objective of HOT to improve and assist mapping for humanitarian aid and disaster relief. Useful open-source data sets of AI-generated building footprints exist (e.g. Microsoft’s global buildings dataset, available through Rapid, and Google’s Open Buildings for Africa and the Global South at large), however, the Machine Learning (ML) models are not currently open-sourced. fAIr, on the other hand, addresses the lack AI models openness by being a fully open source project (HOT Tech Blog, 2022). -While in OSM building footprints mapping is currently supported in most countries through Rapid, "users should take care to ensure adjustments and corrections are made as needed" (Rapid - OSM wiki, 2024); fAIr goes over this issue by reintroducing _the human in the loop_. In fact, at its current state, fAIr allows OSM mappers to create their own local training dataset, train/fine-tune a pre-trained Eff-UNet model, and then map into OSM with the assistance of their own local model. -In its initial release, the performance of the model following training was not assessed, thus the objective of this research is to address this gap. -This proposal describes the research developed in recent months to assess how the ML fine-tuning process performs, investigating the currently used accuracy metric, and comparing against different sets of evaluation metrics. The final aim of this research is to advise on the optimal metric for this building footprints segmentation task. -The research falls within the broader spectrum of research on understanding the fine-tuning process for geographic domain adaptation in image analysis validation (Rainio, Teuho, & Klén, 2024; Maier-Hein et al., 2024). - -**Data and Methodology** -fAIr is a software service that performs semantic segmentation to detect building footprints from openly available local satellite and UAV imagery at high resolution (cm) (OpenAerialMap website, 2017). -In computer vision (CV), semantic segmentation is the task of segmenting an image into semantic meaningful classes, which is performed with convolutional neural networks (CNNs) architectures (Hoeser & Kuenzer, 2020). The deep learning CNN model used in fAIr is called RAMP (Replicable AI for MicroPlanning), and its architecture originates from an Eff-UNet model (RAMP model card, 2020; Baheti, Innani, Gajre, & Talbar, 2020). -With the aim to analyse the current validation accuracy performance and compare against other metrics, an initial literature review on fine-tuning processes for geographic domain adaptation in image analysis validation was performed, which led to outlining a list of candidates for validation metrics (Reinke et al., 2024; Maier-Hein et al., 2024). -In parallel, manual labelling on selected areas of interest (AoI) was carried out on a data set of sixteen urban regions, chosen as the most representative of different grades of urbanity, density, regional characteristics, roof cover types, etc. -The pre-processing of the AoI images was performed for each urban region through fAIr-dev website (fAIr website, 2022), and produced 256x256 georeferenced tiles for both the original RGB images and labelled masks (see example in Figure 3). Then, the ML training was run on all sixteen training datasets using an Nvidia Tesla T4 GPU, for different batch sizes, epochs, and zoom levels. - -**Preliminary results** -Figure 2 shows an example of outcomes of the ML training for four of the urban regions with five types of validation metric (categorical accuracy, precision, recall, IoU - intersection over union, and F1 Score) and categorical cross entropy as the loss function. -The analysis of the research results is still a work in progress. The performance of IoU, the suggested metric for this type of image analysis problem (Reinke et al., 2024), will be assessed against the currently used metric, categorical accuracy, and other commonly used metrics. As a preliminary example of future analysis, Figure 3 shows how categorical accuracy scores compare with other validation metrics at their final value, i.e. the value at the epoch at which the checkpoints are saved, which currently is set at the maximum for the validation categorical accuracy (early stopping). -The different characteristics of the urban regions are also going to be assessed against the performance of the current model. From empirical tests, it is expected that the model has lower accuracy in more dense areas. Fig 4 seems to confirms that, for a specific epoch count (here 20 is shown as an example) and batch size, the performance is higher in urban regions that are more sparse and that present a grid disposition, compared to more dense regions, for all metrics except for Recall. The same figure, but for roof types, suggests that the model performance is lower for cement roof types, as opposed to mixed cover, metal and shingles covers. In terms of urban "type", the results suggest that the current model performs better in the refugee camps regions, and worse peri-urban regions, with higher variability among the validation metrics for semirural and highly urban regions. Further analysis on the statistical significance of these preliminary patterns is under way, with the possibility to extend the research to other urban regions. - -**Conclusions** -To avoid overfitting of the training dataset, early stopping is in place, thus it is important to choose the optimal metric with respect to how fAIr performs, and the research is going to point out the statistical significance of different choices for the model performance and for different urban characteristics. +**Introduction** +Building footprints features are useful in a wide range of applications such as disaster assessment, urban planning, and environmental monitoring (You et al., 2018; Owusu et al., 2021; Yang, Matsushita, & Zhang, 2023), and their identification has been gaining increasing interest and attention from the ML research for Earth Observation (Hoeser, Bachofer, & Kuenzer, 2020). Particularly in the disaster response context, accurate and prompt availability of such information is crucial (Boccardo & Giulio Tonolo, 2015; Deng, 2022; Sun et al., 2022). +fAIr, developed by the Humanitarian OpenStreetMap Team (HOT), a fully open AI-assisted mapping service to generate semi-automated building footprints features, addresses this need (fAIr website, 2022). fAIr stands for “Free and open source AI that is resilient for local contexts, and represents the Responsibility of HOT for local communities and humanitarian mapping", reflecting the objective of HOT to improve and assist mapping for humanitarian aid and disaster relief. Useful open-source data sets of AI-generated building footprints exist (e.g. Microsoft’s global buildings dataset, available through Rapid, and Google’s Open Buildings for Africa and the Global South at large), however, the Machine Learning (ML) models are not currently open-sourced. fAIr, on the other hand, addresses the lack AI models openness by being a fully open source project (HOT Tech Blog, 2022). +While in OSM building footprints mapping is currently supported in most countries through Rapid, "users should take care to ensure adjustments and corrections are made as needed" (Rapid - OSM wiki, 2024); fAIr goes over this issue by reintroducing _the human in the loop_. In fact, at its current state, fAIr allows OSM mappers to create their own local training dataset, train/fine-tune a pre-trained Eff-UNet model, and then map into OSM with the assistance of their own local model. +In its initial release, the performance of the model following training was not assessed, thus the objective of this research is to address this gap. +This proposal describes the research developed in recent months to assess how the ML fine-tuning process performs, investigating the currently used accuracy metric, and comparing against different sets of evaluation metrics. The final aim of this research is to advise on the optimal metric for this building footprints segmentation task. +The research falls within the broader spectrum of research on understanding the fine-tuning process for geographic domain adaptation in image analysis validation (Rainio, Teuho, & Klén, 2024; Maier-Hein et al., 2024). + +**Data and Methodology** +fAIr is a software service that performs semantic segmentation to detect building footprints from openly available local satellite and UAV imagery at high resolution (cm) (OpenAerialMap website, 2017). +In computer vision (CV), semantic segmentation is the task of segmenting an image into semantic meaningful classes, which is performed with convolutional neural networks (CNNs) architectures (Hoeser & Kuenzer, 2020). The deep learning CNN model used in fAIr is called RAMP (Replicable AI for MicroPlanning), and its architecture originates from an Eff-UNet model (RAMP model card, 2020; Baheti, Innani, Gajre, & Talbar, 2020). +With the aim to analyse the current validation accuracy performance and compare against other metrics, an initial literature review on fine-tuning processes for geographic domain adaptation in image analysis validation was performed, which led to outlining a list of candidates for validation metrics (Reinke et al., 2024; Maier-Hein et al., 2024). +In parallel, manual labelling on selected areas of interest (AoI) was carried out on a data set of sixteen urban regions, chosen as the most representative of different grades of urbanity, density, regional characteristics, roof cover types, etc. +The pre-processing of the AoI images was performed for each urban region through fAIr-dev website (fAIr website, 2022), and produced 256x256 georeferenced tiles for both the original RGB images and labelled masks (see example in Figure 3). Then, the ML training was run on all sixteen training datasets using an Nvidia Tesla T4 GPU, for different batch sizes, epochs, and zoom levels. + +**Preliminary results** +Figure 2 shows an example of outcomes of the ML training for four of the urban regions with five types of validation metric (categorical accuracy, precision, recall, IoU - intersection over union, and F1 Score) and categorical cross entropy as the loss function. +The analysis of the research results is still a work in progress. The performance of IoU, the suggested metric for this type of image analysis problem (Reinke et al., 2024), will be assessed against the currently used metric, categorical accuracy, and other commonly used metrics. As a preliminary example of future analysis, Figure 3 shows how categorical accuracy scores compare with other validation metrics at their final value, i.e. the value at the epoch at which the checkpoints are saved, which currently is set at the maximum for the validation categorical accuracy (early stopping). +The different characteristics of the urban regions are also going to be assessed against the performance of the current model. From empirical tests, it is expected that the model has lower accuracy in more dense areas. Fig 4 seems to confirms that, for a specific epoch count (here 20 is shown as an example) and batch size, the performance is higher in urban regions that are more sparse and that present a grid disposition, compared to more dense regions, for all metrics except for Recall. The same figure, but for roof types, suggests that the model performance is lower for cement roof types, as opposed to mixed cover, metal and shingles covers. In terms of urban "type", the results suggest that the current model performs better in the refugee camps regions, and worse peri-urban regions, with higher variability among the validation metrics for semirural and highly urban regions. Further analysis on the statistical significance of these preliminary patterns is under way, with the possibility to extend the research to other urban regions. + +**Conclusions** +To avoid overfitting of the training dataset, early stopping is in place, thus it is important to choose the optimal metric with respect to how fAIr performs, and the research is going to point out the statistical significance of different choices for the model performance and for different urban characteristics. Further research will concentrate on using other factors to help drive the fine-tuning process, like loss regularisation, and will extend the analysis to the prediction performance. diff --git a/sessions/R9CVQD.md b/sessions/R9CVQD.md index 9896923..a8a4832 100644 --- a/sessions/R9CVQD.md +++ b/sessions/R9CVQD.md @@ -1,4 +1,7 @@ --- +youtube: svBAYGvM1rw +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50972-assessing-the-attribute-accuracy-and-logical-consistency-of-road-data-in-openstreetmap +recordings: [{'size': 91, 'length': 1452, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:41:33.861+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82004', 'event_url': 'https://api.media.ccc.de/public/events/f439ff30-da53-5e46-8365-83554188e70c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 46, 'length': 1452, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:28:15.631+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82000', 'event_url': 'https://api.media.ccc.de/public/events/f439ff30-da53-5e46-8365-83554188e70c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 22, 'length': 1452, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-27T19:19:29.978+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/81998', 'event_url': 'https://api.media.ccc.de/public/events/f439ff30-da53-5e46-8365-83554188e70c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 33, 'length': 1452, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:19:26.250+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/81997', 'event_url': 'https://api.media.ccc.de/public/events/f439ff30-da53-5e46-8365-83554188e70c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 71, 'length': 1452, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:15:44.213+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50972-eng-Assessing_the_attribute_accuracy_and_logical_consistency_of_road_data_in_OpenStreetMap_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/81992', 'event_url': 'https://api.media.ccc.de/public/events/f439ff30-da53-5e46-8365-83554188e70c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Assessing the attribute accuracy and logical consistency of road data in OpenStreetMap" code: "R9CVQD" @@ -16,14 +19,14 @@ Our work aims to assess OSM road data quality with a focus on car driving. Curre
-Due to the crowdsourced nature of OpenStreetMap (OSM) and the lack of quality control during the contribution, the data quality issue has become a research focus [1]. Understanding and addressing these data quality issues can facilitate unlocking OSM's full potential for diverse applications. OSM data quality assessment methods can be divided into two broad categories: extrinsic and intrinsic. Extrinsic quality assessment methods compare OSM data with a reference dataset (e.g., authoritative data sources). This is where most initial research on OSM data quality started from [2-4]. Yet, a reference dataset may not always be available. On this ground, researchers called for attention to the intrinsic indicators of OSM data quality [5] and proposed intrinsic data quality measures based on the data, data history, and metadata [5-9]. -It is crucial to acknowledge that the quality of OSM data is not a one-size-fits-all metric. Rather, it heavily depends on the purpose of the application domain, known as "fitness-for-use" [5,10]. The diverse application potentials introduce dynamic data requirements. Navigation is one of the primary application domains in which OSM plays a pivotal role. Among them, vehicular traffic constitutes a significant portion of road usage and has a substantial impact on urban mobility and infrastructure planning. Additionally, the complexities involved in automotive navigation and traffic systems require a higher level of data accuracy and reliability, making it a compelling starting point for investigating intrinsic road data quality. -In the context of car driving, the attribute accuracy and logical consistency of road data are particularly important [11]. Attribute accuracy refers to the correctness and logical coherence of attributes associated with road features, such as speed limits, road classifications, and turn restrictions [12]. Logical consistency ensures that the road network data follows the correct topological rules, such as proper connectivity of different road classes. The attribute accuracy and logical consistency of OSM road data are essential for traffic planning and supporting navigation applications. -To address the challenges of the evaluation of OSM data quality for navigation, when a reference dataset is unavailable, this research narrows its focus on assessing the attribute accuracy and logical consistency of OSM road data. -To assess the attribute accuracy, we first identified important attributes related to car driving, such as road name, road class, surface, speed limit, capacity, height limit, total weight limit, and vehicle type. Then our method assesses the attribute completeness by looking into the tags related to the aforementioned attributes, and whether the relevant information is available. The attribute completeness provides us with a first overview of the attribute data. -In the next step, a set of rules based on country-specific traffic laws is defined, and the relevant attributes are checked against these rules. So far, we have looked into the traffic law in Germany and defined rules for speed limits according to the road classes. Our proposed method looks into the “maxspeed” tag of each road segment, and verifies their value against the rule defined for the corresponding “highway” value. When a mismatch occurs, these road segments are identified and considered as inaccurate. -The inaccuracy of the speed limit is calculated as the number of road segments with an invalid “maxspeed” value divided by the total road segments with “maxspeed”. At the current stage of our work-in-progress, we verified our method in the Heidelberg region, where the inaccuracy rate is very low. -Regarding logical consistency, a set of rules is defined based on country-specific conventions. We acknowledge that different regions in the world have different road construction and road mapping conventions. So far, we have based on our case study in Germany, and defined rules for the values of the “highway” tag. These rules include: the value of the “highway” tag should be consistent along a path; a link road should be connected to its corresponding highway; connection of different classes of roads should be logically consistent (a way with a high level of importance in the road network should not connect directly to a way with a much lower level of importance). -Our work aims to assess OSM road data quality with a focus on car driving. Current work-in-progress proposed indicators to assess attribute accuracy, with a focus on speed limits and methods for estimating the logical consistency of road data. In the next step, we plan to build more rules for speed limits, considering the geometry of the road and their neighbouring zone to infer the speed limit. We will also leverage machine learning methods to set up rule sets for speed limits and road connections for different regions of the world. +Due to the crowdsourced nature of OpenStreetMap (OSM) and the lack of quality control during the contribution, the data quality issue has become a research focus [1]. Understanding and addressing these data quality issues can facilitate unlocking OSM's full potential for diverse applications. OSM data quality assessment methods can be divided into two broad categories: extrinsic and intrinsic. Extrinsic quality assessment methods compare OSM data with a reference dataset (e.g., authoritative data sources). This is where most initial research on OSM data quality started from [2-4]. Yet, a reference dataset may not always be available. On this ground, researchers called for attention to the intrinsic indicators of OSM data quality [5] and proposed intrinsic data quality measures based on the data, data history, and metadata [5-9]. +It is crucial to acknowledge that the quality of OSM data is not a one-size-fits-all metric. Rather, it heavily depends on the purpose of the application domain, known as "fitness-for-use" [5,10]. The diverse application potentials introduce dynamic data requirements. Navigation is one of the primary application domains in which OSM plays a pivotal role. Among them, vehicular traffic constitutes a significant portion of road usage and has a substantial impact on urban mobility and infrastructure planning. Additionally, the complexities involved in automotive navigation and traffic systems require a higher level of data accuracy and reliability, making it a compelling starting point for investigating intrinsic road data quality. +In the context of car driving, the attribute accuracy and logical consistency of road data are particularly important [11]. Attribute accuracy refers to the correctness and logical coherence of attributes associated with road features, such as speed limits, road classifications, and turn restrictions [12]. Logical consistency ensures that the road network data follows the correct topological rules, such as proper connectivity of different road classes. The attribute accuracy and logical consistency of OSM road data are essential for traffic planning and supporting navigation applications. +To address the challenges of the evaluation of OSM data quality for navigation, when a reference dataset is unavailable, this research narrows its focus on assessing the attribute accuracy and logical consistency of OSM road data. +To assess the attribute accuracy, we first identified important attributes related to car driving, such as road name, road class, surface, speed limit, capacity, height limit, total weight limit, and vehicle type. Then our method assesses the attribute completeness by looking into the tags related to the aforementioned attributes, and whether the relevant information is available. The attribute completeness provides us with a first overview of the attribute data. +In the next step, a set of rules based on country-specific traffic laws is defined, and the relevant attributes are checked against these rules. So far, we have looked into the traffic law in Germany and defined rules for speed limits according to the road classes. Our proposed method looks into the “maxspeed” tag of each road segment, and verifies their value against the rule defined for the corresponding “highway” value. When a mismatch occurs, these road segments are identified and considered as inaccurate. +The inaccuracy of the speed limit is calculated as the number of road segments with an invalid “maxspeed” value divided by the total road segments with “maxspeed”. At the current stage of our work-in-progress, we verified our method in the Heidelberg region, where the inaccuracy rate is very low. +Regarding logical consistency, a set of rules is defined based on country-specific conventions. We acknowledge that different regions in the world have different road construction and road mapping conventions. So far, we have based on our case study in Germany, and defined rules for the values of the “highway” tag. These rules include: the value of the “highway” tag should be consistent along a path; a link road should be connected to its corresponding highway; connection of different classes of roads should be logically consistent (a way with a high level of importance in the road network should not connect directly to a way with a much lower level of importance). +Our work aims to assess OSM road data quality with a focus on car driving. Current work-in-progress proposed indicators to assess attribute accuracy, with a focus on speed limits and methods for estimating the logical consistency of road data. In the next step, we plan to build more rules for speed limits, considering the geometry of the road and their neighbouring zone to infer the speed limit. We will also leverage machine learning methods to set up rule sets for speed limits and road connections for different regions of the world. With the proposed assessment, OSM data users can verify road data quality in terms of attribute accuracy and logical consistency, before their intended use. With the evaluation method, we also aim to inform the potential improvement of OSM road data quality, especially for navigation. diff --git a/sessions/SHA79S.md b/sessions/SHA79S.md index 4e1f6a3..fb1ccf7 100644 --- a/sessions/SHA79S.md +++ b/sessions/SHA79S.md @@ -1,4 +1,7 @@ --- +youtube: n82_dEK6tMY +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50848-investigating-corporate-editors-in-openstreetmap +recordings: [{'size': 147, 'length': 1823, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T21:18:41.839+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82030', 'event_url': 'https://api.media.ccc.de/public/events/21ddfb31-7b84-5344-bfae-153fd436271b', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 70, 'length': 1823, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:55:56.051+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82025', 'event_url': 'https://api.media.ccc.de/public/events/21ddfb31-7b84-5344-bfae-153fd436271b', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 27, 'length': 1821, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-28T20:44:07.176+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82022', 'event_url': 'https://api.media.ccc.de/public/events/21ddfb31-7b84-5344-bfae-153fd436271b', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 48, 'length': 1823, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-28T20:44:03.298+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82021', 'event_url': 'https://api.media.ccc.de/public/events/21ddfb31-7b84-5344-bfae-153fd436271b', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 133, 'length': 1823, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-28T20:37:59.137+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50848-eng-Investigating_Corporate_Editors_in_OpenStreetMap_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82017', 'event_url': 'https://api.media.ccc.de/public/events/21ddfb31-7b84-5344-bfae-153fd436271b', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Investigating Corporate Editors in OpenStreetMap" code: "SHA79S" @@ -16,7 +19,7 @@ A discussion of the results of a survey distributed to corporate editors working
-In recent years, OpenStreetMap (OSM) has evolved from being a Volunteered Geographic Information Project to one of the most successful Geospatial Crowdsourcing Platforms in the world. Volunteers, governments, and corporations all make contributions to its global map. Corporate editors (CEs) are the latest entrant in the OSM ecosystem, and their prolific contributions have drawn significant interest from the OSM community as well as the scientific community. In 2018, the OpenStreetMap Foundation introduced a set of Organized Editing Guidelines in response to community outcry related to the edits made by these CEs and a perceived lack of dialogue and transparency between corporations and the larger community. Previous research has focused on the changing landscape of OSM users with the growth of corporate editing, cataloguing the global footprint of corporate editing and the map features that CEs are editing. Others have studied the impacts of having a dedicated workforce that can make significant changes to the map in a very short period of time, as CEs were shown to have different editing habits than volunteer mappers. This study focuses on the CEs themselves, as while other research has explored the impacts of their existence, they have not explored who these editors are, and the reason for their employment. We sought to learn more about the demographic makeup, careers, and motivations and community relationships of these individuals. With these three research objectives, we created an anonymous mixed methods survey that was distributed directly to every listed CE account provided in accordance with the Organized Editing Guidelines on the OSMwiki. Non-exclusive groups were created prior to the collection of results based on previous literature and our research objectives. These groups were then compared to each other using ANOVA and compared to the population using T-tests in R . A non-exclusive typology was also created after results were collected to allow for further analysis of results. This typology was based on the statistical distribution of answers to key questions and it, paired with the groups created based on literature, allowed for a multi-pronged analysis. -The findings reveal that corporate editing in OSM is a legitimate career path and can be more nuanced than simply adding or editing features on the map. Though the most popular employment length was one year, some participants had been employed for upwards of five years. There is a group of CEs that spend almost no time directly editing the map in OSM, yet – on average – have been employed for longer than those who spend the most time editing. Given that over a third of participants mapped in OSM prior to their employment as a CE, it was not surprising that there are ties between CEs and the OSM community, but we found that there was a link between community involvement and job satisfaction, as there was significant overlap between the most satisfied and most involved respondents. When editing, all respondents edited a variety of features, no specialization where a CE would only work with a single feature type was seen. Some editors edited the map before making it a career, some started editing on their free time after getting a job as a corporate editor, and others do not map outside of work. There is also a variety of salary types with an hourly wage being the most popular, but other CEs being paid a monthly or annual salary. A profile of a typical CE was created using the mode of each question’s response and reveals many are enjoying their jobs and would like to continue. There is insight into the workplace by depicting the resources available to editors and a general framework of their work week, with 8-hour days, one project meeting per week, and good relationships between colleagues. There is not much direct interaction between the typical CE and members of the community, but they do use community resources (like OSMwiki) and consider its status as an open project important to their employ in the field. +In recent years, OpenStreetMap (OSM) has evolved from being a Volunteered Geographic Information Project to one of the most successful Geospatial Crowdsourcing Platforms in the world. Volunteers, governments, and corporations all make contributions to its global map. Corporate editors (CEs) are the latest entrant in the OSM ecosystem, and their prolific contributions have drawn significant interest from the OSM community as well as the scientific community. In 2018, the OpenStreetMap Foundation introduced a set of Organized Editing Guidelines in response to community outcry related to the edits made by these CEs and a perceived lack of dialogue and transparency between corporations and the larger community. Previous research has focused on the changing landscape of OSM users with the growth of corporate editing, cataloguing the global footprint of corporate editing and the map features that CEs are editing. Others have studied the impacts of having a dedicated workforce that can make significant changes to the map in a very short period of time, as CEs were shown to have different editing habits than volunteer mappers. This study focuses on the CEs themselves, as while other research has explored the impacts of their existence, they have not explored who these editors are, and the reason for their employment. We sought to learn more about the demographic makeup, careers, and motivations and community relationships of these individuals. With these three research objectives, we created an anonymous mixed methods survey that was distributed directly to every listed CE account provided in accordance with the Organized Editing Guidelines on the OSMwiki. Non-exclusive groups were created prior to the collection of results based on previous literature and our research objectives. These groups were then compared to each other using ANOVA and compared to the population using T-tests in R . A non-exclusive typology was also created after results were collected to allow for further analysis of results. This typology was based on the statistical distribution of answers to key questions and it, paired with the groups created based on literature, allowed for a multi-pronged analysis. +The findings reveal that corporate editing in OSM is a legitimate career path and can be more nuanced than simply adding or editing features on the map. Though the most popular employment length was one year, some participants had been employed for upwards of five years. There is a group of CEs that spend almost no time directly editing the map in OSM, yet – on average – have been employed for longer than those who spend the most time editing. Given that over a third of participants mapped in OSM prior to their employment as a CE, it was not surprising that there are ties between CEs and the OSM community, but we found that there was a link between community involvement and job satisfaction, as there was significant overlap between the most satisfied and most involved respondents. When editing, all respondents edited a variety of features, no specialization where a CE would only work with a single feature type was seen. Some editors edited the map before making it a career, some started editing on their free time after getting a job as a corporate editor, and others do not map outside of work. There is also a variety of salary types with an hourly wage being the most popular, but other CEs being paid a monthly or annual salary. A profile of a typical CE was created using the mode of each question’s response and reveals many are enjoying their jobs and would like to continue. There is insight into the workplace by depicting the resources available to editors and a general framework of their work week, with 8-hour days, one project meeting per week, and good relationships between colleagues. There is not much direct interaction between the typical CE and members of the community, but they do use community resources (like OSMwiki) and consider its status as an open project important to their employ in the field. Unfortunately, we encountered several challenges in reaching out to individual editors as the organizations they work for explicitly prevented them from answering the survey. This had a significant impact on our ability to collect responses, as over half the CE community was made unavailable to this study. Due to low participation numbers, we must establish that our results do not serve as a definite representation of CEs. Low participation was also the rationale for the multi-pronged analysis, as we sought to learn as much as possible from a limited population. Though all CEs reserve the right to not participate in this study, the blanket refusal seen by some corporations is at odds with the autonomous agency which has been a tradition of OSM. At one company, all direct messages sent to any of their CE accounts on OSM redirect to the inbox of their manager, which raises similar questions. While our results may not provide a faithful representation of CEs, our work furthers conversation regarding these workers and broaches the topic of their agency. diff --git a/sessions/TXYEFS.md b/sessions/TXYEFS.md index 0fdd9d2..a6b4d96 100644 --- a/sessions/TXYEFS.md +++ b/sessions/TXYEFS.md @@ -1,4 +1,6 @@ --- +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-49943-the-role-of-crowd-mapping-in-post-emergency-humanitarian-operations +recordings: [{'size': 49, 'length': 574, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T19:10:55.771+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82039', 'event_url': 'https://api.media.ccc.de/public/events/57cf13a6-15f6-5b8d-b8e7-d24e04b29c4c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 23, 'length': 574, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T19:04:55.323+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82036', 'event_url': 'https://api.media.ccc.de/public/events/57cf13a6-15f6-5b8d-b8e7-d24e04b29c4c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 17, 'length': 574, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T18:57:55.120+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82033', 'event_url': 'https://api.media.ccc.de/public/events/57cf13a6-15f6-5b8d-b8e7-d24e04b29c4c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 8, 'length': 574, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-29T18:56:54.920+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82032', 'event_url': 'https://api.media.ccc.de/public/events/57cf13a6-15f6-5b8d-b8e7-d24e04b29c4c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 45, 'length': 574, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T18:55:40.092+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-49943-eng-The_role_of_crowd-mapping_in_post-emergency_humanitarian_operations_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82031', 'event_url': 'https://api.media.ccc.de/public/events/57cf13a6-15f6-5b8d-b8e7-d24e04b29c4c', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "The role of crowd-mapping in post-emergency humanitarian operations" code: "TXYEFS" @@ -16,23 +18,23 @@ Following a theoretical and methodological analysis of the scientific literature
-INTRODUCTION / BACKGROUND -Considering that NGOs and International Organizations have been applying PRA methodologies to community mapping for over two decades without any scientific recognition, we could subscribe to the general opinion that among practitioners, researchers, and activists, the practice of Web-GIS with OSM is more advanced than the underlying theory of its applications [12]. The so-called "digital humanitarianism" can support climate justice by providing tools and platforms for data collection, analysis, and dissemination that empower vulnerable communities to advocate for their rights, mobilize for climate action and advance equitable solutions. Overall, digital humanitarianism can amplify the voices of marginalized communities, enhance transparency and accountability, and promote greater inclusivity in the fight for climate justice. Digital humanitarianism is located at the intersection of new socio-technical practices, a new epistemology, and new institutional relationships [5; 8], as demonstrated by communities like Ushahidi, the Humanitarian OpenStreetMapTeam (HOTOSM), and the Missing Maps. - -PURPOSE OF THE STUDY -The study aims to gain a better understanding of the nature of the link between crowd-mapping and participatory planning by analysing the distinctive features of the application case, the criticalities and problems that emerged, and the possible strategies to be activated to tackle them especially in contexts where people living in rural and remote areas and in peri-urban areas face problems such as inadequate access to essential resources, such as food and water security, and are more exposed to low quality basic services (health and education) and the effects of natural disasters. This fosters inequality, can limit capabilities and promote environmental injustice. - -METHODOLOGY AND FINDINGS -The fieldwork is part of an emergency intervention led by a consortium project combining five NGOs financed by Caritas, with an overall objective of assisting the population impacted by the earthquake that struck in Morocco on September 8 and 9, 2023. As part of this intervention, which calls for various support measures (distribution of family kits, distribution of housing tents and school modules, social-health interventions and psychological support), a humanitarian mapping action is currently being carried out with the help of a group of women belonging to a popular radio station attentive to 'open data'. The project starts from an integrated strategy that brings together humanitarian mapping and future labs, presenting a dynamic approach to addressing social challenges in post-emergency contexts and crisis areas. - -Case study: the contribution to crowd - mapping experimentation (training, definition of a working group, creation of a virtual mapping environment with the use of OSM and Osmand) is investigated, an ongoing process started by OfficianSocialeCOPE (the Research Centre of COPE ONG) and the University of Catania and Palermo (Italy) within the context of a post-emergence project (which will end in July 2024l supporting the victims of the Earthquake of September 2023 in Morocco with an approach to address the perception of individual and collective vulnerability in a rural post-emergency context. -The expected maps are also employed in contrasting contexts, such as in counter-mapping initiatives where indigenous communities (in the case of High Atlas and Sahara villages) seek to regain a certain level of control over ancestral lands and city neighborhoods, resources and services by utilizing participatory mapping methodologies. This makes people aware of their power of pressing issues on local government policies. -Localisation of the territorial landmarks reference points takes into account the WEF (Water, Energy, Food) nexus's provided topics, which included access to fresh food, electricity, and water, as well as other issues that the participants perceive as significant to the neighborhood, (watercourses forests, cultivated areas, potholes, etc. in rural areas, but also small income generating activities potentials). -More specifically, residents, through PGIS mapping tools for on field visit, report issues such as the level of connection of remote areas with other villages and secondary roads, natural and artificial water sources, soil dryness and exposition to drought in High Atlas, as well as associative realities such as cooperatives or Community Based (CSOs) already established or expressing the will to formalise to create income and revenues. -It is critical to consolidate/train the social labs' working groups, which will be made up of territorial representatives and stakeholders from various sectors, such as volunteers, community leaders, and members of local organisations (e.g., muqaddim [neighbourhood or village community leader], kaid [mayor], school teachers, association representatives, headmasters, etc.). Furthermore, the working groups were separated by gender in order to better convey gender-specific demands and requirements. -Through the use of GIS tools (QGIS, Google Earth Pro) and a Web map server (OpenStreetMap), and with the classification of the map contributors' working group, future labs are implemented to share experiences and knowledge on mapping activities and their application in the humanitarian context of reference (PHASE 1 and 2), aiming to plan disaster risk reduction and response and propose development processes strategies (PHASE 2 and 3). The final product to stakeholders includes developing a project outcome using a story-map tool (PHASE 3). - -FINAL DISCUSSION -For the first time, in very remote areas of Morocco, the areas and names of settlements, agricultural and productive land and, above all, areas at low and high risk of natural disasters will be mapped with the help of local knowledge. For the purposes of 'spatial learning, discussion, information exchange, analysis, decision-making and advocacy' [11], many approaches and tools will be used 'to represent people's spatial knowledge'. The primary objective will be to learn how community members define vulnerability and to classify various community stressors. The end result that will be presented to stakeholders will be a combination of satellite imagery, GPS survey locations, participatory mapping and spatial analysis of the geographic information system (GIS), combined with information obtained through interviews and field surveys. The development, georeferencing and visualisation of Indigenous Geographic Knowledge (IGK) will help communities to engage in peer-to-peer conversations and ensure that specific issues and concerns are taken into account by the authorities. Only by considering the participatory process itself could the promoted activity become an example of good governance, i.e. transparent and consensus-based decision-making processes for land management. This is why the different geographical viewpoints of women are of particular interest. The article intends to highlight how PGIS can facilitate the creation and exchange of indigenous ecological and spatial knowledge and improve individual social learning regarding the environment and response to natural disasters and promote development. The fact that the case study was developed in a vulnerable context of North Africa is meant to emphasise that in order to help reduce the digital divide, the lack of attention to research and investigation in the field of digital mapping in Africa compared to the significant progress made in industrialised countries must be taken into consideration. +INTRODUCTION / BACKGROUND +Considering that NGOs and International Organizations have been applying PRA methodologies to community mapping for over two decades without any scientific recognition, we could subscribe to the general opinion that among practitioners, researchers, and activists, the practice of Web-GIS with OSM is more advanced than the underlying theory of its applications [12]. The so-called "digital humanitarianism" can support climate justice by providing tools and platforms for data collection, analysis, and dissemination that empower vulnerable communities to advocate for their rights, mobilize for climate action and advance equitable solutions. Overall, digital humanitarianism can amplify the voices of marginalized communities, enhance transparency and accountability, and promote greater inclusivity in the fight for climate justice. Digital humanitarianism is located at the intersection of new socio-technical practices, a new epistemology, and new institutional relationships [5; 8], as demonstrated by communities like Ushahidi, the Humanitarian OpenStreetMapTeam (HOTOSM), and the Missing Maps. + +PURPOSE OF THE STUDY +The study aims to gain a better understanding of the nature of the link between crowd-mapping and participatory planning by analysing the distinctive features of the application case, the criticalities and problems that emerged, and the possible strategies to be activated to tackle them especially in contexts where people living in rural and remote areas and in peri-urban areas face problems such as inadequate access to essential resources, such as food and water security, and are more exposed to low quality basic services (health and education) and the effects of natural disasters. This fosters inequality, can limit capabilities and promote environmental injustice. + +METHODOLOGY AND FINDINGS +The fieldwork is part of an emergency intervention led by a consortium project combining five NGOs financed by Caritas, with an overall objective of assisting the population impacted by the earthquake that struck in Morocco on September 8 and 9, 2023. As part of this intervention, which calls for various support measures (distribution of family kits, distribution of housing tents and school modules, social-health interventions and psychological support), a humanitarian mapping action is currently being carried out with the help of a group of women belonging to a popular radio station attentive to 'open data'. The project starts from an integrated strategy that brings together humanitarian mapping and future labs, presenting a dynamic approach to addressing social challenges in post-emergency contexts and crisis areas. + +Case study: the contribution to crowd - mapping experimentation (training, definition of a working group, creation of a virtual mapping environment with the use of OSM and Osmand) is investigated, an ongoing process started by OfficianSocialeCOPE (the Research Centre of COPE ONG) and the University of Catania and Palermo (Italy) within the context of a post-emergence project (which will end in July 2024l supporting the victims of the Earthquake of September 2023 in Morocco with an approach to address the perception of individual and collective vulnerability in a rural post-emergency context. +The expected maps are also employed in contrasting contexts, such as in counter-mapping initiatives where indigenous communities (in the case of High Atlas and Sahara villages) seek to regain a certain level of control over ancestral lands and city neighborhoods, resources and services by utilizing participatory mapping methodologies. This makes people aware of their power of pressing issues on local government policies. +Localisation of the territorial landmarks reference points takes into account the WEF (Water, Energy, Food) nexus's provided topics, which included access to fresh food, electricity, and water, as well as other issues that the participants perceive as significant to the neighborhood, (watercourses forests, cultivated areas, potholes, etc. in rural areas, but also small income generating activities potentials). +More specifically, residents, through PGIS mapping tools for on field visit, report issues such as the level of connection of remote areas with other villages and secondary roads, natural and artificial water sources, soil dryness and exposition to drought in High Atlas, as well as associative realities such as cooperatives or Community Based (CSOs) already established or expressing the will to formalise to create income and revenues. +It is critical to consolidate/train the social labs' working groups, which will be made up of territorial representatives and stakeholders from various sectors, such as volunteers, community leaders, and members of local organisations (e.g., muqaddim [neighbourhood or village community leader], kaid [mayor], school teachers, association representatives, headmasters, etc.). Furthermore, the working groups were separated by gender in order to better convey gender-specific demands and requirements. +Through the use of GIS tools (QGIS, Google Earth Pro) and a Web map server (OpenStreetMap), and with the classification of the map contributors' working group, future labs are implemented to share experiences and knowledge on mapping activities and their application in the humanitarian context of reference (PHASE 1 and 2), aiming to plan disaster risk reduction and response and propose development processes strategies (PHASE 2 and 3). The final product to stakeholders includes developing a project outcome using a story-map tool (PHASE 3). + +FINAL DISCUSSION +For the first time, in very remote areas of Morocco, the areas and names of settlements, agricultural and productive land and, above all, areas at low and high risk of natural disasters will be mapped with the help of local knowledge. For the purposes of 'spatial learning, discussion, information exchange, analysis, decision-making and advocacy' [11], many approaches and tools will be used 'to represent people's spatial knowledge'. The primary objective will be to learn how community members define vulnerability and to classify various community stressors. The end result that will be presented to stakeholders will be a combination of satellite imagery, GPS survey locations, participatory mapping and spatial analysis of the geographic information system (GIS), combined with information obtained through interviews and field surveys. The development, georeferencing and visualisation of Indigenous Geographic Knowledge (IGK) will help communities to engage in peer-to-peer conversations and ensure that specific issues and concerns are taken into account by the authorities. Only by considering the participatory process itself could the promoted activity become an example of good governance, i.e. transparent and consensus-based decision-making processes for land management. This is why the different geographical viewpoints of women are of particular interest. The article intends to highlight how PGIS can facilitate the creation and exchange of indigenous ecological and spatial knowledge and improve individual social learning regarding the environment and response to natural disasters and promote development. The fact that the case study was developed in a vulnerable context of North Africa is meant to emphasise that in order to help reduce the digital divide, the lack of attention to research and investigation in the field of digital mapping in Africa compared to the significant progress made in industrialised countries must be taken into consideration. Furthermore, it is shown how important it is to evaluate experiences (both failures and successes) and to develop instructions and strategies to promote best practices in this area, ensuring that the reasoned adoption of the PGIS meets the expectations of different groups in developing countries and does not fall into the dynamics whereby the participatory method may underlie systematic inequalities through unequal and superficial use of PGIS applications, which thus risk being used to legitimise decisions already made by other parties. diff --git a/sessions/TY73TC.md b/sessions/TY73TC.md new file mode 100644 index 0000000..ebb312c --- /dev/null +++ b/sessions/TY73TC.md @@ -0,0 +1,28 @@ +--- +youtube: 1Vf2IeE2uYA +voc: https://media.ccc.de/v/sotm2024-59416-pre-recorded-lightning-talks +recordings: [{'size': 10, 'length': 126, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-59416-eng-Pre-recorded_Lightning_Talks_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T23:35:02.574+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-59416-eng-Pre-recorded_Lightning_Talks_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82055', 'event_url': 'https://api.media.ccc.de/public/events/0020282b-3ca8-570f-9af3-517331fc1220', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 4, 'length': 126, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-59416-eng-Pre-recorded_Lightning_Talks_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T23:33:54.946+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-59416-eng-Pre-recorded_Lightning_Talks_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82054', 'event_url': 'https://api.media.ccc.de/public/events/0020282b-3ca8-570f-9af3-517331fc1220', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 1, 'length': 126, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-59416-eng-Pre-recorded_Lightning_Talks_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-29T23:33:05.627+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-59416-eng-Pre-recorded_Lightning_Talks_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82053', 'event_url': 'https://api.media.ccc.de/public/events/0020282b-3ca8-570f-9af3-517331fc1220', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 3, 'length': 126, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-59416-eng-Pre-recorded_Lightning_Talks_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-29T23:33:02.380+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-59416-eng-Pre-recorded_Lightning_Talks_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82052', 'event_url': 'https://api.media.ccc.de/public/events/0020282b-3ca8-570f-9af3-517331fc1220', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 9, 'length': 126, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-59416-eng-Pre-recorded_Lightning_Talks_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-29T23:31:09.774+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-59416-eng-Pre-recorded_Lightning_Talks_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82051', 'event_url': 'https://api.media.ccc.de/public/events/0020282b-3ca8-570f-9af3-517331fc1220', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] +layout: session +title: "Pre-recorded Lightning Talks" +code: "TY73TC" +speaker_names: ['SotM Working Group'] +affiliations: None +room: "Pre-recorded Lightning Talks" +length: "20" +time: "Sunday, 17:00" +time_iso: "2024-09-08T14:00:00Z" +resources: [] +recording: False +--- + +Pre-recorded lightning talks are short presentations (maximum 5 minutes) about a topic related to OpenStreetMap. + +
+ +## Mapping the Infrastructure for Disaster Risk Reduction with OpenStreetMap, uMap and Wordpress +_by Raquel Dezidério Souto_ + +This web map is part of a research project that aims to provide a platform for mapping official and collaborative data on risk reduction and disasters that have occurred in the state of Rio de Janeiro (Brazil), with the municipality of Maricá as the project's pilot area of interest (AOI). + +Background music: "Science Documentary" by Lexin_Music, https://pixabay.com/music/build-up-scenes-science-documentary-169621/, [Pixabay Content License](https://pixabay.com/service/license-summary/) + diff --git a/sessions/VFUBCD.md b/sessions/VFUBCD.md index ee34c15..dba82af 100644 --- a/sessions/VFUBCD.md +++ b/sessions/VFUBCD.md @@ -1,4 +1,6 @@ --- +voc: https://media.ccc.de/v/state-of-the-map-2024-academic-track-50063-analyzing-the-spatial-distribution-of-fuel-stations-in-harare-zimbabwe-leveraging-openstreetmap-for-disaster-preparedness-mitigation-and-recovery +recordings: [{'size': 61, 'length': 739, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_webm-hd.webm', 'state': 'new', 'folder': 'webm-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:55:55.888+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-hd/sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_webm-hd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82009', 'event_url': 'https://api.media.ccc.de/public/events/1760b414-c784-572d-babf-9becfd41db56', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 28, 'length': 739, 'mime_type': 'video/webm', 'language': 'eng', 'filename': 'sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_webm-sd.webm', 'state': 'new', 'folder': 'webm-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:50:32.725+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/webm-sd/sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_webm-sd.webm', 'url': 'https://api.media.ccc.de/public/recordings/82008', 'event_url': 'https://api.media.ccc.de/public/events/1760b414-c784-572d-babf-9becfd41db56', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 11, 'length': 739, 'mime_type': 'audio/mpeg', 'language': 'eng', 'filename': 'sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_mp3.mp3', 'state': 'new', 'folder': 'mp3', 'high_quality': False, 'width': 0, 'height': 0, 'updated_at': '2024-11-27T19:42:33.760+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/mp3/sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_mp3.mp3', 'url': 'https://api.media.ccc.de/public/recordings/82006', 'event_url': 'https://api.media.ccc.de/public/events/1760b414-c784-572d-babf-9becfd41db56', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 20, 'length': 739, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_sd.mp4', 'state': 'new', 'folder': 'h264-sd', 'high_quality': False, 'width': 720, 'height': 576, 'updated_at': '2024-11-27T19:42:30.265+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-sd/sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_sd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/82005', 'event_url': 'https://api.media.ccc.de/public/events/1760b414-c784-572d-babf-9becfd41db56', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}, {'size': 53, 'length': 739, 'mime_type': 'video/mp4', 'language': 'eng', 'filename': 'sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_hd.mp4', 'state': 'new', 'folder': 'h264-hd', 'high_quality': True, 'width': 1920, 'height': 1080, 'updated_at': '2024-11-27T19:19:13.172+01:00', 'recording_url': 'https://cdn.media.ccc.de/events/sotm/2024/h264-hd/sotm2024-50063-eng-Analyzing_the_Spatial_Distribution_of_Fuel_Stations_in_Harare_Zimbabwe_Leveraging_OpenStreetMap_for_Disaster_Preparedness_Mitigation_and_Recovery_hd.mp4', 'url': 'https://api.media.ccc.de/public/recordings/81996', 'event_url': 'https://api.media.ccc.de/public/events/1760b414-c784-572d-babf-9becfd41db56', 'conference_url': 'https://api.media.ccc.de/public/conferences/sotm2024'}] layout: session title: "Analyzing the Spatial Distribution of Fuel Stations in Harare, Zimbabwe: Leveraging OpenStreetMap for Disaster Preparedness, Mitigation and Recovery" code: "VFUBCD" @@ -16,15 +18,15 @@ Whether they are man-made or natural, disasters pose serious risks to communitie
-Natural or man-made disasters pose serious risks to communities all over the world and frequently have dire repercussions, including the loss of life, destruction of property, and disruption of social order [1]. Fire occurrences are particularly dangerous among these calamities, especially when they include infrastructure such as gasoline stations [2]. The potential for large-scale fire catastrophes underscores the need of ensuring the safety of gasoline station infrastructure, as evidenced by occurrences documented in Zimbabwe [3]. -Petroleum derivatives, such as gasoline, diesel, kerosene, and LPG, have the potential to ignite fires when handled improperly [4]. It is clear that a comprehensive fire danger assessment is necessary, which highlights the need for proactive fire management planning [4]. Between 1993 and 2004, there were around 243 fire-related incidents at fuel service stations worldwide that were recorded. it's evident that these sites present significant risks -Geospatial technology has become an invaluable instrument for disaster preparedness, response, and mitigation as a result of these issues [5]. By offering open data necessary for disaster response and mitigation, initiatives such as Humanitarian OpenStreetMap and the utilization of platforms similar to OpenStreetMap have made substantial progress in these efforts [6]. These systems ensure the availability of high-quality data for efficient mitigation measures and provide quick and open access to geospatial data, facilitating prompt disaster response activities [7]. The OpenStreetMap data consists of many datasets that use points, lines, polygons, and area attributes to represent real-world features. These databases include characteristics that are useful for study, mitigation, recovery, and preparedness for disasters. -Through the use of Geographic Information Systems (GIS) techniques, mapping into and querying the OpenStreetMap Database, this project seeks to overcome the difficulties presented by fire dangers, namely in gasoline station infrastructure. In order to identify danger zones and potential vulnerabilities, the research specifically aims to perform a thorough examination of building footprints, conventional construction standards, and public spaces such as marketplaces, parks, schools, hospitals, houses of worship, and road networks in Harare, Zimbabwe. Additionally, it seeks to map gas stations, obtain exact locations, and extract pertinent data from OpenStreetMap and other sources by utilizing Geographic Information System (GIS) approaches. The study also aims to categorize areas at risk of fire danger according to a number of factors, such as proximity to fuel stations and the position of LPG filling stations according to Zimbabwean government rules and retail premises, as well as other factors identified through spatial analysis. -Additionally, it seeks to offer practical suggestions and solutions for improving public safety and lessening the effects of fire disasters in Harare, Zimbabwe, offering insightful information for initiatives related to disaster preparation, mitigation, and recovery. -to advance resilience and sustainable development in the area while also adding to the scientific understanding of the dangers of fire hazards related to gasoline stations. -This study's methodology combines spatial analytic methodologies, data extraction from OpenStreetMap and other sources, and Geographic Information System (GIS) analysis. -To fully comprehend the gaps that now exist, we will first start by gaining access to the data that is already available on the OpenStreetMap Database. The gasoline stations will then be mapped into the OpenStreetMap database, where pertinent data such as locations and infrastructure aspects will be recorded. This information will then be taken out of OpenStreetMap. The procedure involves extracting comprehensive information on the locations of buildings, roads, and public spaces including playgrounds, marketplaces, hospitals, and schools from the massive OpenStreetMap database. -A thorough examination of the geographic distribution of filling stations, public buildings, and fire service stations will be done using a geographic information system. The objective of this research is to categorize areas at risk of fire hazards according to the Zimbabwean government's standards for the placement of retail and LPG filling stations. These rules include factors such as the distance from fuel stations and other infrastructural concerns. To fully comprehend the spatial distribution of fuel stations in relation to fire stations, residential buildings, and public amenities like schools, hospitals, places of worship, markets, parks, and more, techniques like Euclidean, nearest neighborhood analysis, and geoprocessing analysis will be used. -In order to do the study, the number of buildings in each of the four fire danger risk zones—very high, high, medium, and low risk—will be grouped and examined. In order to determine the number of structures in each of these designated zones, a query to the OpenStreetMap dataset will be made. This will yield important information on the possible effects of fire hazard events on different regions within the research area. +Natural or man-made disasters pose serious risks to communities all over the world and frequently have dire repercussions, including the loss of life, destruction of property, and disruption of social order [1]. Fire occurrences are particularly dangerous among these calamities, especially when they include infrastructure such as gasoline stations [2]. The potential for large-scale fire catastrophes underscores the need of ensuring the safety of gasoline station infrastructure, as evidenced by occurrences documented in Zimbabwe [3]. +Petroleum derivatives, such as gasoline, diesel, kerosene, and LPG, have the potential to ignite fires when handled improperly [4]. It is clear that a comprehensive fire danger assessment is necessary, which highlights the need for proactive fire management planning [4]. Between 1993 and 2004, there were around 243 fire-related incidents at fuel service stations worldwide that were recorded. it's evident that these sites present significant risks +Geospatial technology has become an invaluable instrument for disaster preparedness, response, and mitigation as a result of these issues [5]. By offering open data necessary for disaster response and mitigation, initiatives such as Humanitarian OpenStreetMap and the utilization of platforms similar to OpenStreetMap have made substantial progress in these efforts [6]. These systems ensure the availability of high-quality data for efficient mitigation measures and provide quick and open access to geospatial data, facilitating prompt disaster response activities [7]. The OpenStreetMap data consists of many datasets that use points, lines, polygons, and area attributes to represent real-world features. These databases include characteristics that are useful for study, mitigation, recovery, and preparedness for disasters. +Through the use of Geographic Information Systems (GIS) techniques, mapping into and querying the OpenStreetMap Database, this project seeks to overcome the difficulties presented by fire dangers, namely in gasoline station infrastructure. In order to identify danger zones and potential vulnerabilities, the research specifically aims to perform a thorough examination of building footprints, conventional construction standards, and public spaces such as marketplaces, parks, schools, hospitals, houses of worship, and road networks in Harare, Zimbabwe. Additionally, it seeks to map gas stations, obtain exact locations, and extract pertinent data from OpenStreetMap and other sources by utilizing Geographic Information System (GIS) approaches. The study also aims to categorize areas at risk of fire danger according to a number of factors, such as proximity to fuel stations and the position of LPG filling stations according to Zimbabwean government rules and retail premises, as well as other factors identified through spatial analysis. +Additionally, it seeks to offer practical suggestions and solutions for improving public safety and lessening the effects of fire disasters in Harare, Zimbabwe, offering insightful information for initiatives related to disaster preparation, mitigation, and recovery. +to advance resilience and sustainable development in the area while also adding to the scientific understanding of the dangers of fire hazards related to gasoline stations. +This study's methodology combines spatial analytic methodologies, data extraction from OpenStreetMap and other sources, and Geographic Information System (GIS) analysis. +To fully comprehend the gaps that now exist, we will first start by gaining access to the data that is already available on the OpenStreetMap Database. The gasoline stations will then be mapped into the OpenStreetMap database, where pertinent data such as locations and infrastructure aspects will be recorded. This information will then be taken out of OpenStreetMap. The procedure involves extracting comprehensive information on the locations of buildings, roads, and public spaces including playgrounds, marketplaces, hospitals, and schools from the massive OpenStreetMap database. +A thorough examination of the geographic distribution of filling stations, public buildings, and fire service stations will be done using a geographic information system. The objective of this research is to categorize areas at risk of fire hazards according to the Zimbabwean government's standards for the placement of retail and LPG filling stations. These rules include factors such as the distance from fuel stations and other infrastructural concerns. To fully comprehend the spatial distribution of fuel stations in relation to fire stations, residential buildings, and public amenities like schools, hospitals, places of worship, markets, parks, and more, techniques like Euclidean, nearest neighborhood analysis, and geoprocessing analysis will be used. +In order to do the study, the number of buildings in each of the four fire danger risk zones—very high, high, medium, and low risk—will be grouped and examined. In order to determine the number of structures in each of these designated zones, a query to the OpenStreetMap dataset will be made. This will yield important information on the possible effects of fire hazard events on different regions within the research area. This study seeks to give crucial information for risk and disaster management (preparedness, mitigation, and recovery) by undertaking a thorough investigation of fire hazard threats linked with petrol stations in Harare, Zimbabwe. By employing Geographic Information System (GIS) techniques and utilizing geospatial data from OpenStreetMap, the project aims to improve public safety, lessen the effects of fire disasters, and advance scientific knowledge of fire hazard hazards. Additionally, this study's conclusions and suggestions aim to promote resilience and sustainable development in Harare and beyond. diff --git a/sessions/academic_lightning_talks_1.md b/sessions/academic_lightning_talks_1.md index 341a0ab..95346f4 100644 --- a/sessions/academic_lightning_talks_1.md +++ b/sessions/academic_lightning_talks_1.md @@ -1,4 +1,6 @@ --- +youtube: 8hYxJE_6bGw +youtube: pPXTavUgyb8 layout: session title: "Academic Lightning Talks I" code: "YWH3XD" diff --git a/sessions/academic_lightning_talks_2.md b/sessions/academic_lightning_talks_2.md index 4d53051..c976ecb 100644 --- a/sessions/academic_lightning_talks_2.md +++ b/sessions/academic_lightning_talks_2.md @@ -1,4 +1,6 @@ --- +youtube: XsOlrp4Hsec +youtube: t7GIfiU3ChY layout: session title: "Academic Lightning Talks II" code: "YWH3XD" diff --git a/talks.json b/talks.json index bbca6e7..eac5eaf 100644 --- a/talks.json +++ b/talks.json @@ -2,7 +2,7 @@ "talks": [ { "code": "WTH9FS", - "id": 1073127, + "id": 1073213, "title": "Opening Session", "abstract": "We welcome the OpenStreetMap community in Nairobi but also online to celebrate the international State of the Map conference. This session will provide also some formal instructions and helpful information. For example you will learn how the QA (question and answer) sessions are run. And what we will do on Friday and Saturday evening.", "speakers": [ @@ -13,13 +13,13 @@ "end": "2024-09-06T10:20:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T22:50:37.805079+00:00", + "updated": "2024-09-08T05:57:36.640284+00:00", "state": null, "do_not_record": null }, { "code": "EWNBAV", - "id": 1073128, + "id": 1073214, "title": "UN Maps - Supporting Peace with Open Data", "abstract": "UN Maps is an initiative from the Department of Operational Support at the United Nations which aims not only to enrich topographic and operational data in UN mission areas but also to provide peacekeeping and humanitarian actors with topographic maps, operational geo-information, search and navigation tools, and imagery and street-level base maps. UN Maps is built on both UN internal authoritative geospatial information and open data, especially OpenStreetMap. UN Maps has also built a thriving community, called UN Mappers, around the collection and validation of open geospatial data with contributors from local communities, academia and UN staff in the field.", "speakers": [ @@ -30,49 +30,66 @@ "end": "2024-09-06T10:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.682362+00:00", + "updated": "2024-11-19T18:36:59.781695+00:00", "state": null, "do_not_record": null }, { - "id": 1073131, + "id": 1073218, "title": { "en": "Coffee Break" }, "start": "2024-09-06T08:00:00Z", "end": "2024-09-06T11:30:00+03:00", - "room": 3178 + "room": 3179 }, { - "id": 1073130, + "id": 1073217, "title": { "en": "Coffee Break" }, "start": "2024-09-06T08:00:00Z", "end": "2024-09-06T11:30:00+03:00", - "room": 3177 + "room": 3176 }, { - "id": 1073129, + "id": 1073215, "title": { "en": "Coffee Break" }, "start": "2024-09-06T08:00:00Z", "end": "2024-09-06T11:30:00+03:00", - "room": 3176 + "room": 3178 }, { - "id": 1073132, + "id": 1073216, "title": { "en": "Coffee Break" }, "start": "2024-09-06T08:00:00Z", "end": "2024-09-06T11:30:00+03:00", - "room": 3179 + "room": 3177 + }, + { + "code": "AXHHF3", + "id": 1073220, + "title": "Exporting high-quality Atlas maps in bulk by leveraging OpenStreetMap Data in QGIS", + "abstract": "This workshop is designed to provide participants with practical skills and fundamental knowledge necessary for creating high-quality maps using OpenStreetMap data in QGIS. The course will focus on creating atlases that showcase specific geographic areas by harnessing the power of OSM data. The workshop will provide a comprehensive overview of the entire process involved in atlas creation, including acquiring OSM data, developing a base map, incorporating layers and labels, and exporting the final product. Whether you are an experienced seeking to enhance your skills or a beginner looking to learn new techniques", + "speakers": [ + "SQXFVL" + ], + "track": 4513, + "start": "2024-09-06T11:30:00+03:00", + "end": "2024-09-06T12:30:00+03:00", + "room": 3178, + "duration": 60, + "updated": "2024-09-08T05:57:36.640482+00:00", + "state": null, + "do_not_record": null }, { "code": "A3JTVT", - "id": 1073134, + "id": 1073219, "title": "The OSM Spectrum", "abstract": "OpenStreetMap (OSM) is a collaborative mapping platform with provides open and easy access to its users. It has diverse usability including the general public to governmental and non-governmental organizations. This abstract presents the usage of OSM in general and in the context of Nepal. OSM is used by the local community, the government sector and NGOs, tourism, classrooms, and various projects contributing to the development and gender equality making it a versatile data source. OSM gives a sense of empowerment and responsibility to individuals and contributes to fostering resilience and sustainable development.", "speakers": [ @@ -84,30 +101,13 @@ "end": "2024-09-06T11:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.682545+00:00", - "state": null, - "do_not_record": null - }, - { - "code": "AXHHF3", - "id": 1073133, - "title": "Exporting high-quality Atlas maps in bulk by leveraging OpenStreetMap Data in QGIS", - "abstract": "This workshop is designed to provide participants with practical skills and fundamental knowledge necessary for creating high-quality maps using OpenStreetMap data in QGIS. The course will focus on creating atlases that showcase specific geographic areas by harnessing the power of OSM data. The workshop will provide a comprehensive overview of the entire process involved in atlas creation, including acquiring OSM data, developing a base map, incorporating layers and labels, and exporting the final product. Whether you are an experienced seeking to enhance your skills or a beginner looking to learn new techniques", - "speakers": [ - "SQXFVL" - ], - "track": 4513, - "start": "2024-09-06T11:30:00+03:00", - "end": "2024-09-06T12:30:00+03:00", - "room": 3178, - "duration": 60, - "updated": "2024-09-07T11:32:48.682521+00:00", + "updated": "2024-11-19T18:52:21.435958+00:00", "state": null, "do_not_record": null }, { "code": "C8B93B", - "id": 1073135, + "id": 1073221, "title": "OSMF Funding", "abstract": "The \"OSM Funding\" talk is dedicated to illuminating the management of the OpenStreetMap Foundation as a non-profit organization, reliant on donations and event sponsorship. With a commitment to transparency, the talk aims to provide a clear description of how the OSM Foundation's finances are handled, ensuring the community is informed about fund allocation and usage. By providing a clear understanding of where funds are directed and how they benefit the broader OSM Community, attendees are empowered to build mutual trust with the OSMF. The OSM Foundation endeavors to foster trust and collaboration while maximizing the impact of financial resources for the collective benefit of all of OSM.", "speakers": [ @@ -118,13 +118,13 @@ "end": "2024-09-06T12:20:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.682566+00:00", + "updated": "2024-11-19T20:04:07.169197+00:00", "state": null, "do_not_record": null }, { "code": "LDB3BA", - "id": 1073136, + "id": 1073222, "title": "Sustainable Transport on the Map", "abstract": "Better information leads to better city policy. Unfortunately, many of the world’s cities still lack basic information on their own transport systems, leading to decisions measured against anecdotes rather than data. Using new tools for data processing and display, OpenStreetMap can provide the information that governments need to make better decisions. In this panel we will share recent success stories of cities adopting OSM-based metrics to plan better transport. We will reveal new tools that governments, mappers, and advocates can use. And we will discuss the challenges that still remain and the roles the OSM community can play in overcoming them.", "speakers": [ @@ -135,30 +135,30 @@ "end": "2024-09-06T13:00:00+03:00", "room": 3176, "duration": 60, - "updated": "2024-09-07T11:32:48.682587+00:00", + "updated": "2024-11-19T18:59:28.143898+00:00", "state": null, "do_not_record": null }, { "code": "WCFXG7", - "id": 1073137, + "id": 1073223, "title": "A Replicable Model for OpenStreetMap Training Programs in High Schools", "abstract": "In this presentation, we will share our experience conducting an OpenStreetMap training program with the Kibera Girls' Soccer Academy in Kenya. We will cover various aspects such as the planning process, development of curriculum, hands-on mapping activities, and achieved outcomes. Our aim is to provide practical insights that attendees can use to run similar programs in other schools or regions, promoting greater OpenStreetMap engagement among youth.", "speakers": [ - "KEEP87", - "8DNSXM" + "8DNSXM", + "KEEP87" ], "track": 4517, "start": "2024-09-06T12:30:00+03:00", "end": "2024-09-06T12:50:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T22:48:04.098584+00:00", + "updated": "2024-09-08T05:57:36.640542+00:00", "state": null, "do_not_record": null }, { - "id": 1073140, + "id": 1073224, "title": { "en": "Lunch Break" }, @@ -167,16 +167,16 @@ "room": 3176 }, { - "id": 1073138, + "id": 1073227, "title": { "en": "Lunch Break" }, "start": "2024-09-06T10:00:00Z", "end": "2024-09-06T14:30:00+03:00", - "room": 3179 + "room": 3178 }, { - "id": 1073141, + "id": 1073226, "title": { "en": "Lunch Break" }, @@ -185,17 +185,34 @@ "room": 3177 }, { - "id": 1073139, + "id": 1073225, "title": { "en": "Lunch Break" }, "start": "2024-09-06T10:00:00Z", "end": "2024-09-06T14:30:00+03:00", - "room": 3178 + "room": 3179 + }, + { + "code": "98JMSV", + "id": 1073230, + "title": "Some Assembly Required", + "abstract": "The more detailed our mapping of the real world becomes, the more it becomes apparent that a single node, way or relation is insufficient to represent the complex properties of a real-word object. Streets have many lanes. Buildings have entrances, 3D shapes and POIs inside. And let's not even start talking about the complexity of a major railway station.\r\n\r\nThis talk will take a systematic look at the different ways how complex objects are being mapped in OSM. We explore how editors cope with the complexities of detailed mapping and discuss the implication on how our processing tools need to change to better handle relationships between objects.", + "speakers": [ + "RD7F9S" + ], + "track": 4515, + "start": "2024-09-06T14:30:00+03:00", + "end": "2024-09-06T14:50:00+03:00", + "room": 3176, + "duration": 20, + "updated": "2024-09-08T05:57:36.640722+00:00", + "state": null, + "do_not_record": null }, { "code": "YNEPJM", - "id": 1073143, + "id": 1073228, "title": "Incorporating OpenStreetMap into Academic Curricula: Insights from GeoTE Tanzania's Five-Week Field Training programs with YouthMappers and Academic Partners", "abstract": "Through this initiative, GeoTE Tanzania focuses on integrating OpenStreetMap (OSM) into academic curricula through five-week Field Training sessions with YouthMappers and academic partners. This program emphasizes practical application and problem-solving using OSM data across disciplines such as wildlife, forestry, agriculture, rural and urban development, and environmental studies. By partnering with universities like Sokoine University of Agriculture, GeoTE facilitates hands-on learning experiences that prepare students to address community challenges with geospatial techniques.", "speakers": [ @@ -206,13 +223,13 @@ "end": "2024-09-06T14:50:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.682787+00:00", + "updated": "2024-09-08T05:57:36.640681+00:00", "state": null, "do_not_record": null }, { "code": "FRFJBJ", - "id": 1073144, + "id": 1073229, "title": "Mapping the classroom with Every Door", "abstract": "This is a practical lesson on mapping with Every Door app. The idea for the app is, it's not enough to just map: you should map every single thing you see. So let's train our mapping muscles a bit: it's not a problem that we're inside, treat it as an art class. We will be making art with a map editor. Hopefully nobody would ban us for this haha.", "speakers": [ @@ -223,30 +240,30 @@ "end": "2024-09-06T15:30:00+03:00", "room": 3178, "duration": 60, - "updated": "2024-09-07T11:32:48.682808+00:00", + "updated": "2024-09-08T05:57:36.640702+00:00", "state": null, "do_not_record": null }, { - "code": "98JMSV", - "id": 1073142, - "title": "Some Assembly Required", - "abstract": "The more detailed our mapping of the real world becomes, the more it becomes apparent that a single node, way or relation is insufficient to represent the complex properties of a real-word object. Streets have many lanes. Buildings have entrances, 3D shapes and POIs inside. And let's not even start talking about the complexity of a major railway station.\r\n\r\nThis talk will take a systematic look at the different ways how complex objects are being mapped in OSM. We explore how editors cope with the complexities of detailed mapping and discuss the implication on how our processing tools need to change to better handle relationships between objects.", + "code": "MRQDGE", + "id": 1073232, + "title": "Photo mapping from my village to Pharmacies and Addresses", + "abstract": "**A picture is worth a thousand words**, I am a Pharmacists by training and only discovered the love for technology and maps recently. After discovering OpenStreetMap and taking up mapping based on interest. I share my experience, motivation and how I have used photos to improve OpenStreetMap data in Accra.", "speakers": [ - "RD7F9S" + "3PGXJV" ], - "track": 4515, - "start": "2024-09-06T14:30:00+03:00", - "end": "2024-09-06T14:50:00+03:00", - "room": 3176, + "track": 4512, + "start": "2024-09-06T15:00:00+03:00", + "end": "2024-09-06T15:20:00+03:00", + "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.682764+00:00", + "updated": "2024-09-08T05:57:36.640760+00:00", "state": null, "do_not_record": null }, { "code": "3D9RGU", - "id": 1073145, + "id": 1073231, "title": "Setting the Stage for the Future of Web Based Mapping", "abstract": "Over the years, iD has become a quite capable, versatile and reliable editor for OSM. However, it is currently also facing of a number of challenges: For example, it needs to keep being able to cope with the growing amount and richness of OSM’s map data, as well as to afford the increasingly important task of keeping the map up to date.\r\n\r\nThis talk outlines a proposal to transform iD’s current user interface centered around OSM’s data model into an adaptive user experience that is better tailored towards the needs of individual mappers and outlines an approach of how we can get there as a community.", "speakers": [ @@ -257,30 +274,13 @@ "end": "2024-09-06T15:20:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.682828+00:00", - "state": null, - "do_not_record": null - }, - { - "code": "MRQDGE", - "id": 1073146, - "title": "Photo mapping from my village to Pharmacies and Addresses", - "abstract": "**A picture is worth a thousand words**, I am a Pharmacists by training and only discovered the love for technology and maps recently. After discovering OpenStreetMap and taking up mapping based on interest. I share my experience, motivation and how I have used photos to improve OpenStreetMap data in Accra.", - "speakers": [ - "3PGXJV" - ], - "track": 4512, - "start": "2024-09-06T15:00:00+03:00", - "end": "2024-09-06T15:20:00+03:00", - "room": 3177, - "duration": 20, - "updated": "2024-09-07T11:32:48.682848+00:00", + "updated": "2024-09-08T05:57:36.640741+00:00", "state": null, "do_not_record": null }, { "code": "A7DUFU", - "id": 1073148, + "id": 1073233, "title": "Women in OSM Tech - What worked best for me", "abstract": "This proposal outlines my journey into the tech sector via OpenStreetMap (OSM) as a woman with no prior tech background. I'll share my transformation from beginner mapper to proficient user, skilled in OSM mapping and QGIS for data analysis.In a field where women's representation is limited, my involvement in OSM Tech stands as a testament to breaking barriers and fostering inclusivity—an opportunity provided to me by OpenMap Development Tanzania (OMDTZ). I’ll show the significance of providing equal opportunities and a supportive environment for women in technology in OSM and highlight the potential of OSM as a catalyst for personal and professional advancement.", "speakers": [ @@ -291,13 +291,13 @@ "end": "2024-09-06T15:50:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.682888+00:00", + "updated": "2024-09-28T14:04:48.093004+00:00", "state": null, "do_not_record": null }, { "code": "J9ATMQ", - "id": 1073147, + "id": 1073234, "title": "A Novel Approach to Street-Level Data Collection: Using Customized Bajaji (tricycle) and Mapillary to Enrich OpenStreetMap in Dar es Salaam", "abstract": "In recent years, data creation methods have evolved, incorporating machine learning, AI, deep learning, and virtual reality to streamline processes. However, these advancements have not uniformly benefited communities in developing countries. Nonetheless, OMDTZ tirelessly seeks solutions to ensure more high-quality data are gathered, with low cost and extensive local involvement. One standout initiative involves a customized tricycle, known as bajaj, which is cost-effective, enabling access to streets of varying conditions. Equipped with an affordable street view camera, it collects images used to automate generation of vector data attributes to enrich OpenStreetMap. This session aims to share the experience and process, inspiring other communities to consider similar adaptations.", "speakers": [ @@ -308,85 +308,49 @@ "end": "2024-09-06T15:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.682868+00:00", + "updated": "2024-11-19T19:01:57.611606+00:00", "state": null, "do_not_record": null }, { - "id": 1073149, + "id": 1073238, "title": { "en": "Coffee Break" }, "start": "2024-09-06T13:00:00Z", "end": "2024-09-06T16:30:00+03:00", - "room": 3178 + "room": 3177 }, { - "id": 1073151, + "id": 1073235, "title": { "en": "Coffee Break" }, "start": "2024-09-06T13:00:00Z", "end": "2024-09-06T16:30:00+03:00", - "room": 3179 + "room": 3178 }, { - "id": 1073150, + "id": 1073236, "title": { "en": "Coffee Break" }, "start": "2024-09-06T13:00:00Z", "end": "2024-09-06T16:30:00+03:00", - "room": 3176 + "room": 3179 }, { - "id": 1073152, + "id": 1073237, "title": { "en": "Coffee Break" }, "start": "2024-09-06T13:00:00Z", "end": "2024-09-06T16:30:00+03:00", - "room": 3177 - }, - { - "code": "HCCLGL", - "id": 1073154, - "title": "Hands-on data validation on OSM: best practices and tools", - "abstract": "The workshop is designed for beginner to intermediate mappers to better understand good practices and useful tools while performing data validation on OSM.\r\nDuring the session it will be presented how to discover and interact with mappers in the area to be validated, as well as how to use JOSM plugins and web tools as ResultMaps, Osmose, Whodidit and OSMCha to analyze errors and changesets.\r\nParticipants are requested to bring their laptops and mouses to practice together. Basic understanding of JOSM is welcome but not necessary", - "speakers": [ - "BCLAGF", - "HGCMWV" - ], - "track": 4512, - "start": "2024-09-06T16:30:00+03:00", - "end": "2024-09-06T17:30:00+03:00", - "room": 3178, - "duration": 60, - "updated": "2024-09-07T11:32:48.683029+00:00", - "state": null, - "do_not_record": null - }, - { - "code": "HCCLGL", - "id": 1073155, - "title": "Hands-on data validation on OSM: best practices and tools", - "abstract": "The workshop is designed for beginner to intermediate mappers to better understand good practices and useful tools while performing data validation on OSM.\r\nDuring the session it will be presented how to discover and interact with mappers in the area to be validated, as well as how to use JOSM plugins and web tools as ResultMaps, Osmose, Whodidit and OSMCha to analyze errors and changesets.\r\nParticipants are requested to bring their laptops and mouses to practice together. Basic understanding of JOSM is welcome but not necessary", - "speakers": [ - "BCLAGF", - "HGCMWV" - ], - "track": 4512, - "start": "2024-09-06T16:30:00+03:00", - "end": "2024-09-06T17:30:00+03:00", - "room": 3178, - "duration": 60, - "updated": "2024-09-07T11:32:48.683049+00:00", - "state": null, - "do_not_record": null + "room": 3176 }, { "code": "99HWEX", - "id": 1073156, + "id": 1073241, "title": "Community Capacity Building- Case Study OSM Kenya", "abstract": "Examining the case of OSM Kenya, we showcase and exhibit how initiatives have empowered local communities through open mapping, fostering collaborations, and skill development. We have catalyzed sustainable impact driving positive change across the country and around the world through empowering over 200+ young people who are members of our community. Gaining insights and strategies for enhancing community engagement and capacity within the OpenStreetMap ecosystem in Kenya and beyond borders.", "speakers": [ @@ -398,13 +362,13 @@ "end": "2024-09-06T17:10:00+03:00", "room": 3177, "duration": 40, - "updated": "2024-09-07T11:32:48.683068+00:00", + "updated": "2024-11-19T20:05:51.526372+00:00", "state": null, "do_not_record": null }, { "code": "V3FYDH", - "id": 1073153, + "id": 1073242, "title": "On the Ground", "abstract": "OpenStreetMap is a community project to map the world. Everybody can contribute whatever they want. Or can they? What are the rules that govern what can be mapped in OSM and how? How are we creating a coherent global map and not just a bunch of random data about the world?", "speakers": [ @@ -416,15 +380,51 @@ "end": "2024-09-06T17:10:00+03:00", "room": 3176, "duration": 40, - "updated": "2024-09-07T11:32:48.683009+00:00", + "updated": "2024-09-08T05:57:36.640966+00:00", + "state": null, + "do_not_record": null + }, + { + "code": "HCCLGL", + "id": 1073239, + "title": "Hands-on data validation on OSM: best practices and tools", + "abstract": "The workshop is designed for beginner to intermediate mappers to better understand good practices and useful tools while performing data validation on OSM.\r\nDuring the session it will be presented how to discover and interact with mappers in the area to be validated, as well as how to use JOSM plugins and web tools as ResultMaps, Osmose, Whodidit and OSMCha to analyze errors and changesets.\r\nParticipants are requested to bring their laptops and mouses to practice together. Basic understanding of JOSM is welcome but not necessary", + "speakers": [ + "HGCMWV", + "BCLAGF" + ], + "track": 4512, + "start": "2024-09-06T16:30:00+03:00", + "end": "2024-09-06T17:30:00+03:00", + "room": 3178, + "duration": 60, + "updated": "2024-09-08T05:57:36.640910+00:00", + "state": null, + "do_not_record": null + }, + { + "code": "HCCLGL", + "id": 1073240, + "title": "Hands-on data validation on OSM: best practices and tools", + "abstract": "The workshop is designed for beginner to intermediate mappers to better understand good practices and useful tools while performing data validation on OSM.\r\nDuring the session it will be presented how to discover and interact with mappers in the area to be validated, as well as how to use JOSM plugins and web tools as ResultMaps, Osmose, Whodidit and OSMCha to analyze errors and changesets.\r\nParticipants are requested to bring their laptops and mouses to practice together. Basic understanding of JOSM is welcome but not necessary", + "speakers": [ + "HGCMWV", + "BCLAGF" + ], + "track": 4512, + "start": "2024-09-06T16:30:00+03:00", + "end": "2024-09-06T17:30:00+03:00", + "room": 3178, + "duration": 60, + "updated": "2024-09-08T05:57:36.640929+00:00", "state": null, "do_not_record": null }, { "code": "87HBBY", - "id": 1073158, + "id": 1073243, "title": "Lightning Talks I", - "abstract": "There will be a board where you can sign up for a lightning talks. There are three slots for lightning talks at this conference. Each lightning talk is five minutes long. The topic must be about OpenStreetMap. Prior submission is not required. But if you are not in Nairobi you can send us a prerecorded lightning talk that we will stream during the conference.\r\n\r\n## Discover OSM with free GIS tools in Africa geoportal\r\n_by Esri Eastern Africa_\r\n\r\n## Disaster hackathon 2.0 in Bangladesh\r\n_by Ibtehal_\r\n\r\n## YouthMappas activities an growth in Sri Lanka\r\n_by Sajeevini Sivajothy_\r\n\r\n## Geospatial conference Tanzania (GIS day) November 15-16 2024)\r\n_by Kawamala Antidius_\r\n\r\n## Discover the UN maps learning hub!\r\n_by Sevevin Menavo_\r\n\r\n## Impact of anticipatory mapping in disaster preparedness\r\n_by Jacques Niyigena", + "abstract": "Lightning talks are short presentations (maximum 5 minutes) about a topic related to OpenStreetMap.", "speakers": [ "YNFKER" ], @@ -433,102 +433,103 @@ "end": "2024-09-06T17:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683106+00:00", + "updated": "2024-11-19T19:09:05.441188+00:00", "state": null, "do_not_record": null }, { "code": "MRBEFX", - "id": 1073157, + "id": 1073244, "title": "Strengthening Collaboration between Organizations and Local Communities in West Africa Through the OSMer in Residence Program", "abstract": "Improving the map in OpenStreetMap involves data availability and reliability. Through the operations in which they are involved, organizations have a vast amount of data at their disposal, much of which is confidential and goes against the spirit of Open Data, which is all about sharing. This session will show how the OSMer in Residence program has fostered this paradigm shift through collaboration between HOT's Western and Northern Africa Hub and Médeçins Sans Frontières", "speakers": [ - "Z9CA8S", - "C7C8DL" + "C7C8DL", + "Z9CA8S" ], "track": 4517, "start": "2024-09-06T17:30:00+03:00", "end": "2024-09-06T17:50:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683087+00:00", + "updated": "2024-11-19T20:08:17.582364+00:00", "state": null, "do_not_record": null }, { "code": "B3EH7D", - "id": 1073159, + "id": 1073245, "title": "Mapping Kenya: 15 Years of Map Kibera and beyond", "abstract": "Map Kibera arose from a desire to expand OSM beyond the confines of Europe and North America. In 2009, it pushed the boundaries of what then-new technologies could do. What have the mappers learned over the years? This talk will welcome you to Nairobi and through the ups and downs of mapping in Kenya - from the history of mapping in 20th Kenya, through Map Kibera’s start, into slums and rural parts of Kenya, and finally to current-day Kibera, where mappers are mapping street lights, waste disposal, schools, and more. How has Map Kibera and OSM had a community impact even as drones, satellite technology and AI are revolutionizing mapping? What has changed, and what has remained the same? We will discuss the global impact of Map Kibera, on community-based mapping in OSM and on the general application of technology in developing countries.", "speakers": [ - "KGDXUA", - "7GBE77" + "7GBE77", + "KGDXUA" ], "track": 4512, "start": "2024-09-07T10:00:00+03:00", "end": "2024-09-07T10:40:00+03:00", "room": 3176, "duration": 40, - "updated": "2024-09-07T11:32:48.683125+00:00", + "updated": "2024-09-08T05:57:36.641040+00:00", "state": null, "do_not_record": null }, { - "id": 1073160, + "id": 1073249, "title": { "en": "Coffee Break" }, "start": "2024-09-07T08:00:00Z", "end": "2024-09-07T11:30:00+03:00", - "room": 3177 + "room": 3178 }, { - "id": 1073163, + "id": 1073246, "title": { "en": "Coffee Break" }, "start": "2024-09-07T08:00:00Z", "end": "2024-09-07T11:30:00+03:00", - "room": 3176 + "room": 3177 }, { - "id": 1073162, + "id": 1073247, "title": { "en": "Coffee Break" }, "start": "2024-09-07T08:00:00Z", "end": "2024-09-07T11:30:00+03:00", - "room": 3179 + "room": 3176 }, { - "id": 1073161, + "id": 1073248, "title": { "en": "Coffee Break" }, "start": "2024-09-07T08:00:00Z", "end": "2024-09-07T11:30:00+03:00", - "room": 3178 + "room": 3179 }, { - "code": "PCW97R", - "id": 1073164, - "title": "OSM Wiki editing workshop", - "abstract": "Do you know about a mistake on the OSM wiki?\r\n\r\nHave you wanted to fix it but you are unsure how?\r\n\r\nDo you want to document some already used tag?\r\n\r\nDo you want to add better illustration to some wiki page?\r\n\r\nIs translation of one of wiki pages broken or missing and you want to add it but not sure how to do this?\r\n\r\nAre you confused by OSM Wiki page?\r\n\r\nThis will be a fitting workshop for you! I will help you to fix the problem and edit OSM Wiki.\r\n\r\nIdeally, in future you will be own to make such fix on your own.", + "code": "BXGLWA", + "id": 1073252, + "title": "Cloud-native OSM for Visualization & Analysis", + "abstract": "[Cloud-native approaches and formats](https://cloudnativegeo.org/) are increasingly becoming the defaults for geospatial data analysis, visualisation and distribution. Standards like STAC and formats like GeoParquet, FlatGeobuf and PMTiles are being adopted to meet high volume and performance needs. OpenStreetMap can take advantage of these new approaches to increase adoption, interoperability and solve analysis and visualisation problems that were previously complex. This talk will discuss a few ways to bring cloud-native formats to OSM use-cases and present lessons on building new applications that take advantage of these improvements. Particularly, we will discuss how to use cloud-native approaches to improve OSM validation and change visualization efforts.", "speakers": [ - "ZBGMZE" + "PBXG7S", + "7RHVP9" ], - "track": 4511, + "track": 4515, "start": "2024-09-07T11:30:00+03:00", - "end": "2024-09-07T12:30:00+03:00", - "room": 3178, - "duration": 60, - "updated": "2024-09-07T11:32:48.683240+00:00", + "end": "2024-09-07T11:50:00+03:00", + "room": 3176, + "duration": 20, + "updated": "2024-09-08T05:57:36.641189+00:00", "state": null, "do_not_record": null }, { "code": "VS77B3", - "id": 1073166, + "id": 1073251, "title": "Preparing for disasters with open map data and tools - learning through anticipatory action in Zimbabwe, Liberia and Timor Leste", "abstract": "Historically, the open mapping movement’s disaster focus has been response, but evolving local capacity, insight, technology and partnerships mean new anticipatory action and disaster preparedness open mapping methodologies enable a transition from reactive to proactive approaches to disaster management.\r\n\r\nThis talk explores key findings on the transformative role of open mapping in this topic, demonstrated by three HOT collaborations; Anticipatory Response Program in Zimbabwe, Flood Tracking Project in Liberia, and Mapping for Anticipatory Action in Timor-Leste, plus analysis of post-disaster data demand from NGO and government responders. \r\n\r\nThe talk will also surface insights on how OSM communities can increase their own disaster resilience and preparedness through mapping.", "speakers": [ @@ -540,31 +541,30 @@ "end": "2024-09-07T11:50:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683278+00:00", + "updated": "2024-09-08T05:57:36.641171+00:00", "state": null, "do_not_record": null }, { - "code": "BXGLWA", - "id": 1073165, - "title": "Cloud-native OSM for Visualization & Analysis", - "abstract": "[Cloud-native approaches and formats](https://cloudnativegeo.org/) are increasingly becoming the defaults for geospatial data analysis, visualisation and distribution. Standards like STAC and formats like GeoParquet, FlatGeobuf and PMTiles are being adopted to meet high volume and performance needs. OpenStreetMap can take advantage of these new approaches to increase adoption, interoperability and solve analysis and visualisation problems that were previously complex. This talk will discuss a few ways to bring cloud-native formats to OSM use-cases and present lessons on building new applications that take advantage of these improvements. Particularly, we will discuss how to use cloud-native approaches to improve OSM validation and change visualization efforts.", + "code": "PCW97R", + "id": 1073250, + "title": "OSM Wiki editing workshop", + "abstract": "Do you know about a mistake on the OSM wiki?\r\n\r\nHave you wanted to fix it but you are unsure how?\r\n\r\nDo you want to document some already used tag?\r\n\r\nDo you want to add better illustration to some wiki page?\r\n\r\nIs translation of one of wiki pages broken or missing and you want to add it but not sure how to do this?\r\n\r\nAre you confused by OSM Wiki page?\r\n\r\nThis will be a fitting workshop for you! I will help you to fix the problem and edit OSM Wiki.\r\n\r\nIdeally, in future you will be own to make such fix on your own.", "speakers": [ - "PBXG7S", - "7RHVP9" + "ZBGMZE" ], - "track": 4515, + "track": 4511, "start": "2024-09-07T11:30:00+03:00", - "end": "2024-09-07T11:50:00+03:00", - "room": 3176, - "duration": 20, - "updated": "2024-09-07T11:32:48.683259+00:00", + "end": "2024-09-07T12:30:00+03:00", + "room": 3178, + "duration": 60, + "updated": "2024-09-08T05:57:36.641152+00:00", "state": null, "do_not_record": null }, { "code": "ZHME3F", - "id": 1073168, + "id": 1073253, "title": "Improving data homogeneity across a country", "abstract": "This talk aims to share the efforts of OSM contributors to improve national datasets based on experiences in the Democratic Republic of the Congo. From data analyses to the setup of crowdmapping projects through welcoming new mappers to join and writing documentation. This talk is going to introduce a number of existing tools that proved to be useful in the DRC community.", "speakers": [ @@ -575,13 +575,13 @@ "end": "2024-09-07T12:20:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683316+00:00", + "updated": "2024-11-19T20:10:26.132022+00:00", "state": null, "do_not_record": null }, { "code": "T3CXBD", - "id": 1073167, + "id": 1073254, "title": "MapLibre Tiles: A Next Generation Vector Tiles Format specially designed for OSM data", "abstract": "MapLibre Tiles (MLT) is a new vector tiles format which offers a significant tile size reduction and accelerated decoding performance compared to the de-facto standard Mapbox Vector Tiles (MVT). MLT also adds support for missing features like nested properties, linear referencing and M-values. Our evaluation against MVT on a OpenMapTiles schema based OSM tileset shows a reduction in tile size of nearly up to 80% with even faster decoding times. This talk explains how MLT can be used in combination with OSM data and the advantages it offers.", "speakers": [ @@ -592,13 +592,13 @@ "end": "2024-09-07T12:20:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683297+00:00", + "updated": "2024-09-08T05:57:36.641227+00:00", "state": null, "do_not_record": null }, { "code": "EBMVWS", - "id": 1073169, + "id": 1073255, "title": "OpenStreetMap and the GDPR", "abstract": "The privacy that OpenStreetMap gives to users in its software and programming interface has lagged behind the requirements of the European Union’s General Data Protection Regulation in some respects. We are now taking steps to remedy this and the changes that mappers and API clients will see are discussed here.", "speakers": [ @@ -609,12 +609,12 @@ "end": "2024-09-07T12:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683334+00:00", + "updated": "2024-09-08T05:57:36.641245+00:00", "state": null, "do_not_record": null }, { - "id": 1073171, + "id": 1073256, "title": { "en": "Lunch Break" }, @@ -623,52 +623,54 @@ "room": 3176 }, { - "id": 1073173, + "id": 1073258, "title": { "en": "Lunch Break" }, "start": "2024-09-07T10:00:00Z", "end": "2024-09-07T14:30:00+03:00", - "room": 3177 + "room": 3178 }, { - "id": 1073170, + "id": 1073259, "title": { "en": "Lunch Break" }, "start": "2024-09-07T10:00:00Z", "end": "2024-09-07T14:30:00+03:00", - "room": 3178 + "room": 3179 }, { - "id": 1073172, + "id": 1073257, "title": { "en": "Lunch Break" }, "start": "2024-09-07T10:00:00Z", "end": "2024-09-07T14:30:00+03:00", - "room": 3179 + "room": 3177 }, { - "code": "MJKAC8", - "id": 1073174, - "title": "Download OSM data translated into your language using free software components and standard protocols", - "abstract": "This presentation will introduce a download service of OpenStreetMap GIS layers in English, but also in French for French-speaking areas. In addition to the translation aspect, this service is intended as a proof of concept for an approach that is interoperable, flexible and replicable: it uses open source software components, some of which are supported by OSGeo, and interoperable WMS and WFS protocols of the OGC (Open Geospatial Consortium), while providing detailed OSM data for the countries in question.", + "code": "L7SUBJ", + "id": 1073262, + "title": "Easy Access to ohsome full history OSM contributions using cloud hosted GeoParquet", + "abstract": "This workshop teaches you how you can accelerate OSM data analysis without the need to run your own computing cluster. We will provide a sneak preview about our new cloud hosted ohsome full history contributions data and will show you how you can use it to understand the dynamics in OSM.", "speakers": [ - "HGCMWV" + "E8WPXD", + "JWED7P", + "WABK8C" ], - "track": 4514, + "track": 4515, "start": "2024-09-07T14:30:00+03:00", - "end": "2024-09-07T14:50:00+03:00", - "room": 3177, - "duration": 20, - "updated": "2024-09-07T11:32:48.683445+00:00", + "end": "2024-09-07T15:30:00+03:00", + "room": 3178, + "duration": 60, + "updated": "2024-09-08T05:57:36.641388+00:00", "state": null, "do_not_record": null }, { "code": "HS8SVU", - "id": 1073175, + "id": 1073261, "title": "Meet the OSMF Working Groups", "abstract": "The OSM Foundation is kept running with the help of many volunteers. They look after our servers, the data, the community, the conference, membership and much more. In this session, some of our working groups will introduce themselves. Hear about what they do and how you can help. There will be also plenty of time to ask questions.", "speakers": [ @@ -679,32 +681,30 @@ "end": "2024-09-07T15:10:00+03:00", "room": 3176, "duration": 40, - "updated": "2024-09-07T11:32:48.683464+00:00", + "updated": "2024-09-08T05:57:36.641370+00:00", "state": null, "do_not_record": null }, { - "code": "L7SUBJ", - "id": 1073176, - "title": "Easy Access to ohsome full history OSM contributions using cloud hosted GeoParquet", - "abstract": "This workshop teaches you how you can accelerate OSM data analysis without the need to run your own computing cluster. We will provide a sneak preview about our new cloud hosted ohsome full history contributions data and will show you how you can use it to understand the dynamics in OSM.", + "code": "MJKAC8", + "id": 1073260, + "title": "Download OSM data translated into your language using free software components and standard protocols", + "abstract": "This presentation will introduce a download service of OpenStreetMap GIS layers in English, but also in French for French-speaking areas. In addition to the translation aspect, this service is intended as a proof of concept for an approach that is interoperable, flexible and replicable: it uses open source software components, some of which are supported by OSGeo, and interoperable WMS and WFS protocols of the OGC (Open Geospatial Consortium), while providing detailed OSM data for the countries in question.", "speakers": [ - "E8WPXD", - "JWED7P", - "WABK8C" + "HGCMWV" ], - "track": 4515, + "track": 4514, "start": "2024-09-07T14:30:00+03:00", - "end": "2024-09-07T15:30:00+03:00", - "room": 3178, - "duration": 60, - "updated": "2024-09-07T11:32:48.683483+00:00", + "end": "2024-09-07T14:50:00+03:00", + "room": 3177, + "duration": 20, + "updated": "2024-09-08T05:57:36.641351+00:00", "state": null, "do_not_record": null }, { "code": "A3Y3BC", - "id": 1073177, + "id": 1073263, "title": "State of the art in combining OSM and Linked Data", "abstract": "Thousands of Linked [Open] Data sources and knowledge graphs allow to access an enormous amount of structured interconnected data with built in interoperability. This talk explains the basics of Linked Data and offers an overview about the potential its combination with OSM has and the most popular methods available for linking, extracting, combining and querying data from OSM and Linked Data sources.", "speakers": [ @@ -715,13 +715,13 @@ "end": "2024-09-07T15:20:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683503+00:00", + "updated": "2024-09-08T05:57:36.641406+00:00", "state": null, "do_not_record": null }, { "code": "3ZU3ZR", - "id": 1073179, + "id": 1073264, "title": "Open mapping through tropical forest biodiversity conservation", "abstract": "The botanical collection Arboretum and Palmetum Leon Morales Soto houses 412 species from 64 botanical families, totaling 4892 individuals. The mapping carried out by the SAGEMA chapter of YouthMappers allowed sharing valuable information about Colombian flora with the university community, facilitating its conservation and recognition through the integration of collection data into OSM. The project aims to promote the conservation of threatened tropical ecosystems through open mapping. It involved the participation of 12 students and a training strategy through open workshops to replicate the project in other Latin American regions.", "speakers": [ @@ -732,13 +732,13 @@ "end": "2024-09-07T15:50:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683540+00:00", + "updated": "2024-09-08T05:57:36.641424+00:00", "state": null, "do_not_record": null }, { "code": "ZVVQTA", - "id": 1073178, + "id": 1073265, "title": "The Journal of Importing Open Data Address in Taiwan into OpenStreetMap", "abstract": "Importing a government-release open data dataset is an important data source for OpenStreetMap. I will talk about the experience of the OpenStreetMap Taiwan community importing tasks. I will describe the methods and the challenges we face during the whole import process. We have already dealt with 9 counties and cities' address datasets, and looking forward to dealing with more datasets released by other local government agencies in the future.", "speakers": [ @@ -749,39 +749,39 @@ "end": "2024-09-07T15:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683522+00:00", + "updated": "2024-09-08T05:57:36.641443+00:00", "state": null, "do_not_record": null }, { - "id": 1073182, + "id": 1073268, "title": { "en": "Coffee Break" }, "start": "2024-09-07T13:00:00Z", "end": "2024-09-07T16:30:00+03:00", - "room": 3176 + "room": 3179 }, { - "id": 1073181, + "id": 1073266, "title": { "en": "Coffee Break" }, "start": "2024-09-07T13:00:00Z", "end": "2024-09-07T16:30:00+03:00", - "room": 3177 + "room": 3176 }, { - "id": 1073180, + "id": 1073267, "title": { "en": "Coffee Break" }, "start": "2024-09-07T13:00:00Z", "end": "2024-09-07T16:30:00+03:00", - "room": 3179 + "room": 3177 }, { - "id": 1073183, + "id": 1073269, "title": { "en": "Coffee Break" }, @@ -790,25 +790,25 @@ "room": 3178 }, { - "code": "8XCQJB", - "id": 1073184, - "title": "OSMF board – what are they even doing?", - "abstract": "If you have ever wondered what OSMF and OSMF board are doing and why they exist it is a good presentation for you.\r\nWill include a brief overview (as promised in the title) of what they are doing, reason for their existence and why you may want to care about them. And why you may want join the board or one of working groups.\r\nPresented by OSMF board member.", + "code": "HVVYM7", + "id": 1073272, + "title": "Generating Ways with the Strava Heatmap", + "abstract": "The Strava Global Heatmap visualizes aggregated public GPS traces, guiding athletes worldwide in planning their routes by highlighting popular paths. This presentation demonstrates how the Heatmap, in conjunction with our routing engine, can be utilized to identify and fill in missing ways in OpenStreetMap (OSM). We will discuss an algorithmic strategy for creating generated pathways and introduce a prototype of an interface that facilitates the easy integration of these pathways into OSM. We will showcase how Strava's Heatmap can promote OSM's goal of developing a more comprehensive global map, highlighting a mutually beneficial relationship between the two platforms.", "speakers": [ - "ZBGMZE" + "HHN9VA" ], - "track": 4511, + "track": 4512, "start": "2024-09-07T16:30:00+03:00", "end": "2024-09-07T16:50:00+03:00", - "room": 3176, + "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683655+00:00", + "updated": "2024-09-08T05:57:36.641587+00:00", "state": null, "do_not_record": null }, { "code": "HLR7MM", - "id": 1073186, + "id": 1073271, "title": "Build an OpenStreetMap walking tour with a free and open source video game", "abstract": "Minetest Classroom is a free and open source (https://github.com/ubc-minetest-classroom/minetest_classroom) educational, voxel-based sandbox video game that supports the ability to create digital twins from geospatial data, including OpenStreetMap data. In this hands-on workshop, you will learn how to create your own walking tour from OpenStreetMap data with this powerful game. Participants will be able to join a multiplayer server and experience an OpenStreetMap world first-hand. We will also discuss possible lesson plans for teachers looking to engage students with OpenStreetMap, the possibilities for multi-sensory video game cartography more generally, and the future of creating an OpenStreetMap editor in a video game.", "speakers": [ @@ -819,32 +819,32 @@ "end": "2024-09-07T17:30:00+03:00", "room": 3179, "duration": 60, - "updated": "2024-09-07T11:32:48.683693+00:00", + "updated": "2024-09-08T05:57:36.641568+00:00", "state": null, "do_not_record": null }, { - "code": "HVVYM7", - "id": 1073185, - "title": "Generating Ways with the Strava Heatmap", - "abstract": "The Strava Global Heatmap visualizes aggregated public GPS traces, guiding athletes worldwide in planning their routes by highlighting popular paths. This presentation demonstrates how the Heatmap, in conjunction with our routing engine, can be utilized to identify and fill in missing ways in OpenStreetMap (OSM). We will discuss an algorithmic strategy for creating generated pathways and introduce a prototype of an interface that facilitates the easy integration of these pathways into OSM. We will showcase how Strava's Heatmap can promote OSM's goal of developing a more comprehensive global map, highlighting a mutually beneficial relationship between the two platforms.", + "code": "8XCQJB", + "id": 1073270, + "title": "OSMF board – what are they even doing?", + "abstract": "If you have ever wondered what OSMF and OSMF board are doing and why they exist it is a good presentation for you.\r\nWill include a brief overview (as promised in the title) of what they are doing, reason for their existence and why you may want to care about them. And why you may want join the board or one of working groups.\r\nPresented by OSMF board member.", "speakers": [ - "HHN9VA" + "ZBGMZE" ], - "track": 4512, + "track": 4511, "start": "2024-09-07T16:30:00+03:00", "end": "2024-09-07T16:50:00+03:00", - "room": 3177, + "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683674+00:00", + "updated": "2024-09-08T05:57:36.641550+00:00", "state": null, "do_not_record": null }, { "code": "SYRTRW", - "id": 1073187, + "id": 1073273, "title": "Lightning Talks II", - "abstract": "There will be a board where you can sign up for a lightning talks. There are three slots for lightning talks at this conference. Each lightning talk is five minutes long. The topic must be about OpenStreetMap. Prior submission is not required. But if you are not in Nairobi you can send us a prerecorded lightning talk that we will stream during the conference.\r\n\r\n## E-Comappers activities and growth in Rwanda\r\n_by Liliane Nishimirwe_\r\n\r\n## Hot CWG mentorship\r\n_by Benedicta Ohene_\r\n\r\n## Youthmappers activities and growth in Sri Lanka (2021-2024)\r\n_by Sajeevini Sivajothy_\r\n\r\n## #DEI in OSM - Ladies in maps Zimbabwe\r\n_by Letwin Pondo_\r\n\r\n## Microgrants program in Latin America\r\n_by Maya Low_\r\n\r\n## My journey in OSM: Youth mappers Tanzania\r\n_by Iman Seleman_", + "abstract": "Lightning talks are short presentations (maximum 5 minutes) about a topic related to OpenStreetMap.", "speakers": [ "YNFKER" ], @@ -853,13 +853,13 @@ "end": "2024-09-07T17:20:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T13:04:26.335186+00:00", + "updated": "2024-11-20T17:35:29.982512+00:00", "state": null, "do_not_record": null }, { "code": "N7TGMA", - "id": 1073188, + "id": 1073274, "title": "Catching OSM Up with External Data with a Workflow and Tools for Conflation and Validation", "abstract": "This report outlines a project to improve the workflow for integrating external open datasets into OpenStreetMap (OSM), ensuring compliance with import guidelines. The process includes tools for conflating data with OSM, supported by roles and tasks specific to this workflow. The AllThePlaces project supports this by extracting and mapping open (government) data to the OSM schema. A new tool, \"DiffedPlaces\", is proposed to automate diffs, perform data matching with an improved machine learning algorithm, and host the results. In addition, the existing OSM Conflator tool set, enhanced with a web-based data validation application, will be connected to DiffedPlaces.", "speakers": [ @@ -870,30 +870,13 @@ "end": "2024-09-07T17:20:00+03:00", "room": 3177, "duration": 20, - "updated": "2024-09-07T11:32:48.683731+00:00", - "state": null, - "do_not_record": null - }, - { - "code": "XUJWAM", - "id": 1073190, - "title": "openrouteservice version 8 - Experiences and insights from 10+ years of running and providing a global OSM-driven, free and open-source routing engine", - "abstract": "Starting as a small research project at the University of Bonn and later the University of Heidelberg at around 2008, Openrouteservice has been steadily growing since. This ensures that now almost 120,000 users get free and equal access to basic mobility solutions every day. With the release of version 8, this conference talk will give you an exclusive behind-the-scenes look at almost a decade of OpenStreetMap-driven open-source software development and delivery. Our successes and challenges, and how we stayed true to our values, providing free and open-source software as a non-profit organization.", - "speakers": [ - "8RD9TG" - ], - "track": 4514, - "start": "2024-09-08T09:30:00+03:00", - "end": "2024-09-08T09:50:00+03:00", - "room": 3176, - "duration": 20, - "updated": "2024-09-07T11:32:48.683769+00:00", + "updated": "2024-09-08T05:57:36.641624+00:00", "state": null, "do_not_record": null }, { "code": "98YGWG", - "id": 1073189, + "id": 1073276, "title": "Get to know OSGeo and expand Your Open Mapping Toolkit", "abstract": "Are you familiar with OpenStreetMap but want to take your geospatial skills to the next level? This workshop introduces you to the Open Source Geospatial Foundation (OSGeo) and how its various software projects interact with OpenStreetMap data. This will help you to unlock new possibilities for analysis, visualization, and more.\r\n\r\nThrough a hands-on session using OSGeoLive, participants will:\r\n- Explore OSGeo platforms like QGIS, PostGIS, and OpenLayers.\r\n- Discover how these tools integrate with OpenStreetMap data through hands-on exercises.", "speakers": [ @@ -904,13 +887,30 @@ "end": "2024-09-08T10:30:00+03:00", "room": 3178, "duration": 60, - "updated": "2024-09-07T11:32:48.683751+00:00", + "updated": "2024-09-08T09:11:47.410516+00:00", + "state": null, + "do_not_record": null + }, + { + "code": "XUJWAM", + "id": 1073275, + "title": "openrouteservice version 8 - Experiences and insights from 10+ years of running and providing a global OSM-driven, free and open-source routing engine", + "abstract": "Starting as a small research project at the University of Bonn and later the University of Heidelberg at around 2008, Openrouteservice has been steadily growing since. This ensures that now almost 120,000 users get free and equal access to basic mobility solutions every day. With the release of version 8, this conference talk will give you an exclusive behind-the-scenes look at almost a decade of OpenStreetMap-driven open-source software development and delivery. Our successes and challenges, and how we stayed true to our values, providing free and open-source software as a non-profit organization.", + "speakers": [ + "8RD9TG" + ], + "track": 4514, + "start": "2024-09-08T09:30:00+03:00", + "end": "2024-09-08T09:50:00+03:00", + "room": 3176, + "duration": 20, + "updated": "2024-09-08T05:57:36.641642+00:00", "state": null, "do_not_record": null }, { "code": "NHZVNW", - "id": 1073191, + "id": 1073277, "title": "How to develop your own style of OpenMapTiles with your favorite editor?", "abstract": "This presentation introduces how to develop your own style of OpenMapTiles for MapLibre GL from scratch with *your favorite editor*.\r\n\r\n- Introduce of OpenMapTiles schema.\r\n- Introduce of Charites to use your favorite editor.\r\n- Introduce of other tools to compile JSON format for MapLibre GL.\r\n\r\nThis presentation describes with how to use command line tools to create MapLibre GL style.\r\nI recommend to use UNIX based operation system or Raspberry Pi.\r\nThe editors supports VS Code, Emacs, or Vim.", "speakers": [ @@ -921,15 +921,15 @@ "end": "2024-09-08T10:20:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683788+00:00", + "updated": "2024-09-08T05:57:36.641679+00:00", "state": null, "do_not_record": null }, { "code": "ZZTZRB", - "id": 1073200, + "id": 1073278, "title": "Lightning Talks III", - "abstract": "There will be a board where you can sign up for a lightning talks. There are three slots for lightning talks at this conference. Each lightning talk is five minutes long. The topic must be about OpenStreetMap. Prior submission is not required. But if you are not in Nairobi you can send us a prerecorded lightning talk that we will stream during the conference.\r\n\r\n## Campus Guide: Enhance campus navigation through accurate and updated OSM maps\r\n_by Victor Ademoyero_\r\n\r\n## Mapswipe for web\r\n_by Geoffrey Kateregga_\r\n\r\n## Mapping activities and impact in Uganda by geo-youthmappers\r\n_by Umar Katomgole_\r\n\r\n## OSM and OpentherialMap data for machine learning\r\n_by Remígio Chilaule_\r\n\r\n## Essentials for a geospatial entrepreneur\r\n_by Antidius Kawamala_\r\n\r\n## Perspective of women participation in OSM (Brief insights of sunray conducted in March 2023\r\n_by Benedicta Ohere_", + "abstract": "Lightning talks are short presentations (maximum 5 minutes) about a topic related to OpenStreetMap.", "speakers": [ "YNFKER" ], @@ -938,66 +938,49 @@ "end": "2024-09-08T10:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-08T05:54:05.974681+00:00", + "updated": "2024-11-24T19:37:23.319798+00:00", "state": null, "do_not_record": null }, { - "id": 1073194, + "id": 1073282, "title": { "en": "Coffee Break" }, "start": "2024-09-08T08:00:00Z", "end": "2024-09-08T11:30:00+03:00", - "room": 3177 + "room": 3178 }, { - "id": 1073193, + "id": 1073281, "title": { "en": "Coffee Break" }, "start": "2024-09-08T08:00:00Z", "end": "2024-09-08T11:30:00+03:00", - "room": 3176 + "room": 3179 }, { - "id": 1073195, + "id": 1073280, "title": { "en": "Coffee Break" }, "start": "2024-09-08T08:00:00Z", "end": "2024-09-08T11:30:00+03:00", - "room": 3179 + "room": 3176 }, { - "id": 1073196, + "id": 1073279, "title": { "en": "Coffee Break" }, "start": "2024-09-08T08:00:00Z", "end": "2024-09-08T11:30:00+03:00", - "room": 3178 - }, - { - "code": "PRQKRX", - "id": 1073197, - "title": "The Current State of Collaboration between Digital Twin and OSM", - "abstract": "In recent years, advancements in 3D city models have been instrumental in urban planning and public engagement. In Japan, over 200 cities have adopted open digital twin data in CityGML format as promoted by Project PLATEAU of the Ministry of Land, Infrastructure, Transport and Tourism. This initiative, detailed in Binyu et al.'s research and the 3D City Index report, involves collaboration with the global OpenStreetMap community. Utilizing open database license ODbL, the integration of digital twin data with OpenStreetMap has been explored since 2022, aiming to enhance the global adoption of 3D city models and showcase the benefits of collaborative urban development.", - "speakers": [ - "EDWH9Q" - ], - "track": 4515, - "start": "2024-09-08T11:30:00+03:00", - "end": "2024-09-08T11:50:00+03:00", - "room": 3176, - "duration": 20, - "updated": "2024-09-07T11:32:48.683920+00:00", - "state": null, - "do_not_record": null + "room": 3177 }, { "code": "YNBJGQ", - "id": 1073198, + "id": 1073284, "title": "The worst and best of OpenStreetMap in Ghana (Africa)", "abstract": "Africa is huge, publicly available imagery in OSM might not always be up-to-date but massive data is being created with old imagery in many parts of the continent. Using Ghana as a case study we will dive into this rabbit hole, see and learn to improve data quality in OpenStreetMap.", "speakers": [ @@ -1008,13 +991,30 @@ "end": "2024-09-08T12:30:00+03:00", "room": 3178, "duration": 60, - "updated": "2024-09-07T11:32:48.683939+00:00", + "updated": "2024-09-08T05:57:36.641823+00:00", + "state": null, + "do_not_record": null + }, + { + "code": "PRQKRX", + "id": 1073283, + "title": "The Current State of Collaboration between Digital Twin and OSM", + "abstract": "In recent years, advancements in 3D city models have been instrumental in urban planning and public engagement. In Japan, over 200 cities have adopted open digital twin data in CityGML format as promoted by Project PLATEAU of the Ministry of Land, Infrastructure, Transport and Tourism. This initiative, detailed in Binyu et al.'s research and the 3D City Index report, involves collaboration with the global OpenStreetMap community. Utilizing open database license ODbL, the integration of digital twin data with OpenStreetMap has been explored since 2022, aiming to enhance the global adoption of 3D city models and showcase the benefits of collaborative urban development.", + "speakers": [ + "EDWH9Q" + ], + "track": 4515, + "start": "2024-09-08T11:30:00+03:00", + "end": "2024-09-08T11:50:00+03:00", + "room": 3176, + "duration": 20, + "updated": "2024-11-19T19:31:28.413976+00:00", "state": null, "do_not_record": null }, { "code": "Z8F8RB", - "id": 1073199, + "id": 1073285, "title": "Do we need 11 000 shop=* values?", "abstract": "About work on reducing one of minor problems of OpenStreetMap: rare, unclear and confusing tag values. Such as for example shop=mięsny\r\n\r\nHow cleanup of such tags may help? Why it is dangerous to make this kind of edits? How it can be useful and how it can be problematic or annoying?\r\n\r\nHow it can be done so benefits are much greater than damages?\r\n\r\nWhat kind of help would be welcome?", "speakers": [ @@ -1025,15 +1025,15 @@ "end": "2024-09-08T12:20:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.683958+00:00", + "updated": "2024-09-08T05:57:36.641842+00:00", "state": null, "do_not_record": null }, { "code": "8NU7CS", - "id": 1073192, + "id": 1073286, "title": "Lightning Talks IV", - "abstract": "There will be a board where you can sign up for a lightning talks. There are three slots for lightning talks at this conference. Each lightning talk is five minutes long. The topic must be about OpenStreetMap. Prior submission is not required. But if you are not in Nairobi you can send us a prerecorded lightning talk that we will stream during the conference.\r\n\r\n## Hot course in OSM data use (new course!)\r\n_by Sam Colchester_\r\n\r\n## OSM Malawi: Insights into the contributions of the OSM community\r\n_by Priscilla Kapolo_\r\n\r\n## Hot Open Summit 2324\r\n_by Geoffrey Kateregga_\r\n\r\n## The grwth of OSM community in Zambia (Local knowledge mappis)\r\n_by Priscovia Ng'ambi_\r\n\r\n## Using OSM in urban planning of informal settlements\r\n_by Rem ígio Chilaule_\r\n\r\n## Find an efficient way foe field mapping & data collection\r\n_by Micheal Kaluba_\r\n\r\n## OSM Malawi: Insights into the contributions of the OSM community\r\n_by Priscilla Kapolo_\r\n\r\n## Hot Open Summit 2024\r\n_by Geoffrey Kateregga_\r\n\r\n## The grwth of OSM community in Zambia (Local knowledge mappis)\r\n_by Priscovia Ng'ambi_\r\n\r\n## Using OSM in urban planning of informal settements\r\n_by Remígio Chilaule_\r\n\r\n## Find an efficient way for field mapping & data collection\r\n_by Micheal Kaluba_", + "abstract": "Lightning talks are short presentations (maximum 5 minutes) about a topic related to OpenStreetMap.", "speakers": [ "YNFKER" ], @@ -1042,30 +1042,30 @@ "end": "2024-09-08T12:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-08T05:54:13.292289+00:00", + "updated": "2024-11-24T19:53:57.331118+00:00", "state": null, "do_not_record": null }, { - "id": 1073202, + "id": 1073288, "title": { "en": "Lunch Break" }, "start": "2024-09-08T10:00:00Z", "end": "2024-09-08T14:30:00+03:00", - "room": 3177 + "room": 3178 }, { - "id": 1073204, + "id": 1073287, "title": { "en": "Lunch Break" }, "start": "2024-09-08T10:00:00Z", "end": "2024-09-08T14:30:00+03:00", - "room": 3178 + "room": 3177 }, { - "id": 1073201, + "id": 1073289, "title": { "en": "Lunch Break" }, @@ -1074,7 +1074,7 @@ "room": 3179 }, { - "id": 1073203, + "id": 1073290, "title": { "en": "Lunch Break" }, @@ -1083,83 +1083,83 @@ "room": 3176 }, { - "code": "SC7HYF", - "id": 1073205, - "title": "Go Out And Map", - "abstract": "So you want to improve the map of your village or city. How do you do that — install Mapillary and go cycling? Print a map and use a pen to draw over it? Install an editor app and go tapping buttons? Just try to remember everything and bring it home to map in JOSM? Let's see what tools we have and how to make the best map with no money and lots of enthusiasm.", + "code": "TQXSFP", + "id": 1073292, + "title": "From Source to Map: Strategies for Integrating External Data into OpenStreetMap", + "abstract": "Maintaining data quality while uploading large datasets to OpenStreetMap from external sources like KoboToolbox can feel overwhelming. This workshop tackles that challenge head-on! We'll guide participants through the process of integrating the data into OSM, ensuring its integrity every step of the way. Participants will master data conversion techniques to bridge the gap between external collection formats and OSM's structure. They will learn how to avoid duplicates and data loss while maintaining accuracy during upload using the JOSM editor. By the end, they will be equipped to confidently contribute valuable community data to OpenStreetMap and empower their fellow mappers.", "speakers": [ - "TJ9EBM" + "MBQG7X" ], "track": 4512, "start": "2024-09-08T14:30:00+03:00", - "end": "2024-09-08T14:50:00+03:00", - "room": 3176, - "duration": 20, - "updated": "2024-09-07T11:32:48.684139+00:00", + "end": "2024-09-08T15:30:00+03:00", + "room": 3178, + "duration": 60, + "updated": "2024-09-08T05:57:36.641991+00:00", "state": null, "do_not_record": null }, { - "code": "TQXSFP", - "id": 1073206, - "title": "From Source to Map: Strategies for Integrating External Data into OpenStreetMap", - "abstract": "Maintaining data quality while uploading large datasets to OpenStreetMap from external sources like KoboToolbox can feel overwhelming. This workshop tackles that challenge head-on! We'll guide participants through the process of integrating the data into OSM, ensuring its integrity every step of the way. Participants will master data conversion techniques to bridge the gap between external collection formats and OSM's structure. They will learn how to avoid duplicates and data loss while maintaining accuracy during upload using the JOSM editor. By the end, they will be equipped to confidently contribute valuable community data to OpenStreetMap and empower their fellow mappers.", + "code": "SC7HYF", + "id": 1073291, + "title": "Go Out And Map", + "abstract": "So you want to improve the map of your village or city. How do you do that — install Mapillary and go cycling? Print a map and use a pen to draw over it? Install an editor app and go tapping buttons? Just try to remember everything and bring it home to map in JOSM? Let's see what tools we have and how to make the best map with no money and lots of enthusiasm.", "speakers": [ - "MBQG7X" + "TJ9EBM" ], "track": 4512, "start": "2024-09-08T14:30:00+03:00", - "end": "2024-09-08T15:30:00+03:00", - "room": 3178, - "duration": 60, - "updated": "2024-09-07T11:32:48.684158+00:00", + "end": "2024-09-08T14:50:00+03:00", + "room": 3176, + "duration": 20, + "updated": "2024-09-08T05:57:36.641972+00:00", "state": null, "do_not_record": null }, { "code": "C8UWGW", - "id": 1073207, + "id": 1073293, "title": "OSMF Board AMA", "abstract": "OpenStreetMap Foundation Board Ask Us Anything (i.e. AMA). We will take questions from the audience, or other questions that people can submit before the event, and we will talk about and answer them. We can talk about the past actions of the board, and what future plans we have.", "speakers": [ - "JKGQ9U", - "JBAK7J", + "RD7F9S", + "ZBGMZE", "9LCYEQ", "FKFUVW", + "JKGQ9U", + "JBAK7J", "KBUVZX", - "ZBGMZE", - "3XXVZL", - "RD7F9S" + "3XXVZL" ], "track": 4517, "start": "2024-09-08T15:00:00+03:00", "end": "2024-09-08T16:00:00+03:00", "room": 3176, "duration": 60, - "updated": "2024-09-07T11:32:48.684176+00:00", + "updated": "2024-09-08T05:57:36.642009+00:00", "state": null, "do_not_record": null }, { - "id": 1073210, + "id": 1073295, "title": { "en": "Coffee Break" }, "start": "2024-09-08T13:00:00Z", "end": "2024-09-08T16:30:00+03:00", - "room": 3177 + "room": 3179 }, { - "id": 1073211, + "id": 1073294, "title": { "en": "Coffee Break" }, "start": "2024-09-08T13:00:00Z", "end": "2024-09-08T16:30:00+03:00", - "room": 3179 + "room": 3177 }, { - "id": 1073208, + "id": 1073296, "title": { "en": "Coffee Break" }, @@ -1168,7 +1168,7 @@ "room": 3178 }, { - "id": 1073209, + "id": 1073297, "title": { "en": "Coffee Break" }, @@ -1178,7 +1178,7 @@ }, { "code": "8ZVKZV", - "id": 1073212, + "id": 1073298, "title": "Closing Session", "abstract": "We say goodby to this year's State of the Map conference and to Nairobi. You will see some impressions of the conference and we say thank you to all volunteers and to the local team of Nairobi. We hope that we can already announce the venue of State of the Map 2025.", "speakers": [ @@ -1189,7 +1189,24 @@ "end": "2024-09-08T16:50:00+03:00", "room": 3176, "duration": 20, - "updated": "2024-09-07T11:32:48.684293+00:00", + "updated": "2024-09-08T05:57:36.642119+00:00", + "state": null, + "do_not_record": null + }, + { + "code": "TY73TC", + "id": 1122352, + "title": "Pre-recorded Lightning Talks", + "abstract": "Pre-recorded lightning talks are short presentations (maximum 5 minutes) about a topic related to OpenStreetMap.", + "speakers": [ + "YNFKER" + ], + "track": 5009, + "start": "2024-09-08T17:00:00+03:00", + "end": "2024-09-08T17:20:00+03:00", + "room": 3731, + "duration": 20, + "updated": "2024-11-29T20:48:28.290706+00:00", "state": null, "do_not_record": null }, @@ -1370,8 +1387,8 @@ "title": "What happens when VGI is threatened? A systems perspective analysis of the events behind the introduction of rate limiting in OpenStreetMap", "abstract": "This talk presents a systems perspective analysis of events in October-November 2023 which started with large-scale vandalism of OpenStreetMap data in Israel and ended with the introduction of rate limiting. Noting how the project reacted in face of this unique situation and the undermining of its basic assumptions facilitating the project helps uncover resilience- and vulnerability-inducing mechanisms within it, to characterize the range of possible external influences on the project, and assess their possible outcomes.", "speakers": [ - "3UBLLA", - "HN77EN" + "HN77EN", + "3UBLLA" ], "track": null, "start": "2024-09-08T15:00:00+03:00", @@ -1409,7 +1426,7 @@ "room": 3177 } ], - "version": "1.0.8", + "version": "1.0.9", "timezone": "Africa/Nairobi", "event_start": "2024-09-06", "event_end": "2024-09-08", @@ -1517,6 +1534,15 @@ "description": { "en": "Workshops held online inside our conference platform 'venueless'" } + }, + { + "id": 3731, + "name": { + "en": "Pre-recorded Lightning Talks" + }, + "description": { + "en": "Virtual room for pre-recorded lightning talks" + } } ], "speakers": [