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 have always loved the website Learn X in Y minutes, which provides short crash courses in several dozen programming languages plus additional topics such as set theory and git. Its home page tells us “Take a whirlwind tour of your next favorite language”; I’ll bet it’s especially popular with applicants on their way to job interviews where languages that are new to them are in the job description.

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.

During the course of my recent blog posts What is RDF?, What is RDFS?, What else can I do with RDFS?, and Taxonomy management with SKOS, some readers wondered if I would do a “What is OWL?” followup. I recommended to one inquirer that he read pages 39-41 and 263 - 269 of Learning SPARQL; I think that provides a pretty good introduction to OWL’s history and how to do some of the set-based logic that was an important part of its original intent.