diff --git a/doc/wiki/owl-vocabulary.md b/doc/wiki/owl-vocabulary.md new file mode 100644 index 0000000..84e41e0 --- /dev/null +++ b/doc/wiki/owl-vocabulary.md @@ -0,0 +1,48 @@ +# OWL Vocabulary + + + +## Basics + +[Source](https://protege.stanford.edu/publications/ontology_development/ontology101.pdf) + +- **ontology** | the "grammar" ("formal description" = structure) + of your knowledge base; + the entirety of concepts described + + - consists of **classes**, **slots** and **facets** + +- **class** | "all wines are …"; + set of **slots** that instances of this **class** share + + - EXAMPLE: wines + - can have **subclasses** + - also called "concept" + +- **subclass** | more specific class inside a (super)class + + - EXAMPLE: shiraz wines + +- **slot** | property/feature/attribute… of a **class** + + - can have **facets** + - also called "role", "property" + +- **facet** | restriction of a slot + + - also called "role restriction" + +- **instance** | the actual thing + + - EXAMPLE a specific glass of wine + +- **knowledge base** | + the fancier word for graph-oriented database; + "An ontology together with a set of individual instances of classes + constitutes a knowledge base. + In reality, there is a fine line where the ontology ends + and the knowledge base begins." diff --git a/doc/wiki/resources.md b/doc/wiki/resources.md new file mode 100644 index 0000000..03233c8 --- /dev/null +++ b/doc/wiki/resources.md @@ -0,0 +1,109 @@ +# Resources + + + + +## Unsorted + +### Julieta + +The field that you might be looking for is called "ontology engineering" in the Semantic Web. +Over the past years, +there have been many methodologies that have been defined +to specify a methodological framework for developing ontologies/vocabularies +either individually or collaboratively. + +On the one hand, +I would recommend to read about the modelling languages in the Semantic Web. +There are books that help understand both the RDF(S)/OWL constructs +and the foundational knowledge: + +- The Semantic Web primer: + (1) +- Semantic Web for the working ontologist: + (2) + +But maybe these books might go into too many details, +especially, since you might not need to exploit all the constructs +of e.g. OWL for your Wikibase ontology; +and Wikibase has its own data model. +So, you might find the following resources more useful, +to understand how knowledge engineers tend to solve the problem +of conceptualizing/modelling the domain: + +- Technical report by Natasha Noy on "A Guide to Creating Your First Ontology": + (3) +- A paper on the Neon Ontology Engineering methodology + that helps you define competency questions + (i.e., the information needs that your ontology needs to cover): + (4) + +The pointer I mentioned in the last event +is a repository with existing ontologies that one can (re-)use -- +like an open data portal, +but for vocabularies (5) .\ +It might be useful to get the URIs of classes and/or properties in these ontologies to, +for instance, type your entities +(i.e., add a statement of the shape `entity rdf:type external_type` +or `entity wdt:p31 external_type`. +But you can also develop your ontology +and then map or align it to existing ones. +The reason why one does that, +is to integrate your data set and ontology with others, +hence, weave the linked dataspace. + +Besides that, +a book that I would totally recommend is the Linked Data book: +(6) +because it gives a very good overview of best practices +on preparing and publishing data as Linked Data, +including data links and vocabularies. + +I realize that you said "guide \[...\] for people outside the field?", +and these are resources to on-board people in Semantic Web ontology engineering. +I don't know if there are resources tailored in an easier/non-technical way, +but I actually think that esp. (3) and (6) are written in a really clear way +and one can use such materials to learn how to follow useful +and well-thought methodologies. +Of course, +learning about these might require looking up further resources, +but I think that is true for any learning activity and topic. :) +I think it is important to look into the base technologies, +to avoid the wild population of data that doesn't follow ground considerations +(e.g., mixing "instance of" and "subclass-of") and hence, +keep good standards for data quality. +Else, the data consumption step will encounter the problems - +my2c. :) + +## Best Practices + +### publishing RDF vocabularies + +- http://www.w3.org/TR/swbp-vocab-pub/ + +## Software + +### Ontology Development Environment + + + +## Platforms and tool related resources + +### Defining ontologies + +- [Utility Evaluation of Tools for Collaborative Development and Maintenance of Ontologies]( + https://www.researchgate.net/publication/224193217_Utility_Evaluation_of_Tools_for_Collaborative_Development_and_Maintenance_of_Ontologies) +- [ontologies for biological & biomedical use cases](http://obofoundry.org/) +- [ontology for biological & biomedical use cases data sharing](http://www.ontobee.org/) +- [product ontology](http://www.productontology.org/) + +[LOV - Reusable vocabularies](https://lov.linkeddata.es/dataset/lov) + +### Operations + +- [Semantic MediaWiki vs Wikibase vs Cargo]( + https://professional.wiki/en/articles/managing-data-in-mediawiki)