Prompt #1 at Biodiversity Next workshop: Issues (perceived or actual) with citizen science data

[eellwood]

[Context: At the biodiversity_next conference workshop, we asked participants to discuss citizen science data quality issues and write responses on post its. These are the responses.]

• Hard to compare between users -- different experiences, abilities
• All data have issues
• Non-systematic collection of data
• People are not experts and make errors when identifying species
• Citizen scientists don't follow instructions
• All data not collected by scientists are bad
• No measure of effort in biodiversity recording
• Trade-off between educational value and scientific value
• Trade-off between fun and work
• Biased in space and time
• Inaccurate species identification
• Bias for interesting-looking species
• Problems are project level
• No way to estimate user expertise
• Prejudiced perception of citizen scientist capabilities vs paid employees
• Lack of "skill"
• Lack of recognition that citizen science data includes highly standardized data collection
• Poor identification
• Lack of guides/guidelines and standards
• Inconsistencies
• People use common names for different species
• Misidentification
• No trust in knowledge of citizen scientists
• Variable and unknown quality of datapoints
• Quality increases/changes as people learn
• Lack of scientific attitude, misuse of scientific methods, ethics, etc.
• Lack of quality control of data and data collectors