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.

The following blog entries give a brief introduction to the RDF data model, the most important of the other W3C standards that build on it, and what people do with those standards:

When I first heard about the AWS Graph Explorer I assumed that it was a cloud-based tool for use with Neptune, the AWS cloud-based triplestore. After I read Fan Li’s First Impressions of the AWS Graph Explorer I realized that you can install this open source tool locally and point it at any SPARQL endpoint you want, so I cranked up Jena Fuseki on my laptop, loaded some data into it, and installed the Graph Explorer.

I recently wondered “could I run a Python script that includes the rdflib library on my Samsung Android phone?” Five minutes later, I was doing it, and about three of those minutes were spent installing Python.

I recently asked on Twitter about the availability of command line OWL processors. I got some leads, but most would have required a little coding or integration work on my part. I decided that a small project that I did with the OWL-RL Python library a few years ago gave me a head start on just creating my own OWL command line processor in Python. It was pretty easy.