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doc/wiki/owl-vocabulary.md

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+# OWL Vocabulary
+
+<!--
+SPDX-FileCopyrightText: 2024 Robin Vobruba <[email protected]>
+
+SPDX-License-Identifier: CC0-1.0
+-->
+
+## 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."

doc/wiki/resources.md

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+# Resources
+
+<!--
+SPDX-FileCopyrightText: 2024 Robin Vobruba <[email protected]>
+
+SPDX-License-Identifier: CC0-1.0
+-->
+
+
+## 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) <https://mitpress.mit.edu/books/semantic-web-primer-second-edition>
+- Semantic Web for the working ontologist:
+  (2) <http://workingontologist.org/>
+
+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) <https://protege.stanford.edu/publications/ontology_development/ontology101.pdf>
+- 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) <https://link.springer.com/chapter/10.1007/978-3-642-24794-1_2>
+
+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) <https://lov.linkeddata.es/dataset/lov/>.\
+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) <http://linkeddatabook.com/editions/1.0/>
+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
+
+<https://protege.stanford.edu/products.php>
+
+## 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)