O’Reilly books such as Learning SPARQL have an errata page where anyone can submit corrections for the book, and I appreciate all entries. Some are just basic typo misspellings, which is embarrassing. Some are examples that no longer work because a certain SPARQL endpoint is no longer up or, in several cases, because DBpedia entries got revised to describe resources using different properties than they did when the book was published.

I asked ChatGPT and Copilot to parse my two favorite home-grown OWL examples, do the appropriate inferencing, and show me the results, and I was impressed.

(This may look like a long blog entry, but it’s mostly sample schemas, data, and shapes. It should be a quick read.)

It’s easy enough for a SPARQL query to specify that you only want literal values that are tagged with a particular spoken language such as English or French. I had a more complex condition to express recently that has happened to me fairly often: how do I retrieve all the data for a particular resource except the literals tagged in a foreign language? I want all the triples with object property values, and I want all the ones with literal values, regardless of type, unless they are tagged…

In my book Learning SPARQL I often use a query for all the triples in a dataset (that is, all the triples in the default graph and all the triples in any named graphs) that I now realize needs some revision to be more accurate.

SPARQL Anything is an open source tool that lets you use SPARQL to query data in a long list of popular formats: XML, JSON, CSV, HTML, Excel, Text, Binary, EXIF, File System, Zip/Tar, Markdown, YAML, Bibtex, DOCx, and PPTx. It has a lot of great documentation and features, but I’ll start here with an example of it in action.

For a long time I’ve thought that it would be fun to use SPARQL queries of Wikidata to create music playlists that can be played back. While researching last month’s blog entry Use SPARQL to query for movies, then watch them I learned about the P724 Internet Archive ID property, and that turned out to be an excellent hook for finding Wikidata audio recordings that we can listen to.