Using the AWS Graph Explorer with Fuseki and local datasets

An open source visual graph navigator.

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.

Learn RDF in Y minutes

Where X = RDF

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.

My command line OWL processor

With most of the credit going to to Ivan Herman.

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.

You probably don't need OWL

And if you do there's a simple way to prove it.

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.

What else can I do with RDFS?

Schemas can be a little fancier and even more useful with no need for OWL.

In my last blog entry, What is RDFS?, I described how the RDF Schema language lets you define RDF vocabularies, with the definitions themselves being RDF triples. We saw how simple class and property name definitions in a schema can, as machine-readable documentation for a dataset’s structure, provide greater interoperability for data and applications built around the same domain. Today we’ll look at how RDF schemas can store additional kinds of valuable information to add to what we…