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:

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.

OriginTrail is doing one of the most interesting combinations of blockchain technology and RDF that I have seen. In November I spoke with CTO and co-founder Branimir Rakić.

Justin Dowdy recently created an open source project to convert the metadata in a git repository to RDF, and I’ve been having some fun with it. Before getting into the details, as a brief demo I’ll start with a sample SPARQL query that I did to list all of the 2019 commits in my misc github repo:

There are a few tutorials out there about how to start up your own free-tier Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instance and then run your own publicly available web server. I’ve planned for a while to try this with a Jena Fuseki triplestore and SPARQL endpoint, but I postponed it because I thought it might be complicated. It turned out to be pretty easy.

Sometimes a question pops into my head that, although unrelated to computers, could likely be answered with a SPARQL query. I don’t necessarily know the query off the top of my head and have to work it out. I’m going to discuss an example of one that I worked out and the steps that I took, because I wanted to show how I navigated the Wikidata data model to get what I wanted.

Two recent articles describe a fascinating use of SPARQL to improve data quality in a knowledge graph at the successful grocery delivery service Instacart. On Reliability Scores for Knowledge Graphs (pdf) is a short paper submitted to the 2022 ACM Web Conference in Lyon and a longer piece on Instacart’s tech blog is titled Red Means Stop. Green Means Go: A Look into Quality Assessment in Instacart’s Knowledge Graph.