We would like to present our open-source toolkit that enables communities to collaboratively maintain SKOS vocabularies using Excel and GitHub, demonstrating how the use of familiar tools can lower barriers to semantic web adoption.
Abstract:
Maintaining SKOS vocabularies collaboratively is hard. RDF/turtle syntax intimidates domain experts. Manual validation is error-prone. Tracking changes and discussions scattered across emails is chaotic. Result? Many communities avoid creating controlled vocabularies altogether.
We built an open-source toolkit that simplified the process: contributors edit terms in Excel spreadsheets, submit via GitHub pull requests, and automated workflows handle everything else – SKOS conversion, SHACL validation, documentation generation, and publishing with persistent URIs and content negotiation.
Why Excel? Familiar to everyone. Why GitHub? It provides version control with complete history tracking, structured discussions via issues/PRs, free hosting, automatic Zenodo publishing and increasingly, built-in AI assistance for contributors and maintainers. The toolkit (Python package + repository template) is domain-agnostic – originally developed for a catalysis vocabulary, but reusable by any community.
@David_Linke Thanks for your lightning talk. I like the approach,w ith SkoHub we follow a very similar Git(Hub).based approach for collaboratively maintaining SKOS vocabs, although we still require someone to edit a turtle file. I am curious: Had you considered using SkoHub? if yes, what were the reasons against it?
I cannot remember exactly, but I think that we did not find SkoHub in late 2021. Also for us the ease of contributing was most relevant which led us to pick vocexcel. - Our users/contributors could not write RDF/turtle directly. Our voc4cat-tool started as fork of vocexcel but in the meantime most code has been rewritten and we have added a lot of extra functionality. Now 80% of the commits in voc4cat-tool are from us. The GitHub automation in voc4cat-template is completely our own work.
Another aspect in tool selection was that Python is preferred over JavaScript in natural sciences because of its strong support for data analysis & ML. So many know Python but only a few know JS.
I first became aware of SkoHub when your SWIB24-Workshop was announced.
I will probably try your static HTML page generator for us and will test if we pass your SHACL schema. In voc4cat we adopted the vocpub-profile but it has limitations and we need to extend it to implement our ideas.