canadian spelling

docs/Data_Standardization/index.md

@@ -4,7 +4,7 @@ title: Data Standardisation
 nav_order: 6
 ---
 
-# Data Standardization
+# Data Standardisation
 {: .no_toc }
 
 ## Table of Contents
@@ -66,7 +66,7 @@ If anticipated early in the project design cycle, data schema components can be
   * Project file names and folder structure should be standardized.
   * Regardless of whether a data schema is reusing elements from other schemas, it is important to impose attribute and table [naming conventions](https://climatesmartagcollab.github.io/Documentation-en/Data_Standardization/schemas.html) on its home-grown components.  This is done mainly to avoid issues in applying or developing software scripts for validation, transformation, and/or database interaction.
 
-## Training resources ###
+## Training resources
 TBD
 
 Authors: Damion Dooley

docs/Data_Standardization/ontology.md

@@ -45,17 +45,17 @@ A hierarchical organization of terms also enables using branches of an ontology
 ### Relations between entity kinds
 Naturally an ontology needs a language of relations between classes (called "object properties") such as "located in" or "part of" and a way to use them in expressing logical statements, called axioms, that must be true for an entity to match to some given class. There is also some functionality (using "data properties") for associating specific values or ranges to class axioms (e.g. "pi 'has value' "3.1415927"^^xsd:decimal).
 
-### Free-text definition
-A class should have a free-text definition which reflects in plain language the logic of any axioms it has, or if no axioms exist, at least helps the reader to recognize what is included or excluded from its category of entity.  This style of definition is called the Aristotelian genus-differentiae form which reference a class's parent class and goes on to differentiate the kinds of entity it matches from those which its siblings would match.
-
-### Multilingual (also by way of synonymy lookup tables)
-Just as an ontology term has a label and free-text definition, it may also have language variants of those, enabling it to be displayed in multiple languages.
+### Textual definition
+A class should have a textual definition which reflects in plain language the logic of any important axioms it has, or if no such axioms exist, at least helps the reader to recognize what is included or excluded from its category of entity.  This style of definition is called the Aristotelian genus-differentiae form which reference a class's parent class and goes on to differentiate the kinds of entity it matches from those which its siblings would match.  OBO Foundry has more advice about [definitions](https://obofoundry.org/principles/fp-006-textual-definitions.html).
 
 ### Curation standards
-Terms are explained in the singular, are provided in a single language like English, and are lowercase except for proper noun parts.
+Terms are explained in the singular, are provided in a primary language like English, and are lowercase except for proper noun parts.  (The singular requirement allows curators (or computers) to fashion plural terms with reference to singular ones - and their characteristics, distinguishing characteristics of an item from characteristics of a group of items.)
+
+### Synonyms and Multilingual labels
+Just as an ontology term has a label and textual definition, it may also have synonyms and language variants of those, improving its findability in free text search engines, and enabling it to be displayed in multiple languages. 
 
 ### Authorship
-Credit is provided for term curators and definition sources.
+Contributor credits are provided for term curators and definition sources.
 
 ## Data Schemas: Database view and ontology view
 A Separation of concern ...

docs/Data_Standardization/schemas.md

@@ -1,11 +1,11 @@
 ---
 layout: default
 title: Data Schema Standardisation
-parent: Data Standardization
+parent: Data Standardisation
 nav_order: 2
 ---
 
-# Data Schema Standardization
+# Data Schema Standardisation
 {: .no_toc }
 
 ## Table of Contents
@@ -75,7 +75,7 @@ We use the term "structured vocabulary" (also known as controlled vocabulary) to
 ## Sources of standardized attributes
 Ontology terms might be precise in terms of describing a thing that is measured, but not how it is measured.  Data schema attributes often go further in specifying datatype values.  Standardized attributes are found in e.g. flat [NCBI BioSample](https://www.ncbi.nlm.nih.gov/biosample/docs/packages/) repository standards and more structured [Phenopacket standards](https://phenopacket-schema.readthedocs.io/).  More details on using structured vocabulary including ontologies to standardize data is provided in the [ontology](https://github.com/ClimateSmartAgCollab/Documentation-en/blob/main/docs/Data_Standardization/ontology.md) section.
 
-## Training resources ###
+## Training resources
 TBD
 
 Authors: Damion Dooley