[simongray]

If you get job where you need to merge graph data from a bunch of different sources, you will likely run into the semantic web stack. The semantic web stack is basically a bunch of technologies for building graph databases and sharing graph data across domains. It isn't some huge network of interlinked data sources like originally envisioned, but it is definitely not dead. I think the concept of graph databases is still something people are only beginning to discover the uses for. Most people only know of the initial XML serialisation of RDF and OWL which rightfully made people skeptical. Nowadays, the most common serialisation format is TURTLE which is basically just a subset of SPARQL and it is very readable.

In fact, the underlying technologies are all quite mature (triplestore implementations and the RDF, SPARQL, OWL, etc. standards) and used heavily in certain domains, such as biology and language. The standards are designed for easy serialisation and interoperability which is the antithesis of the "modern" walled garden and/or commercial API approach of the big Internet companies, although they also use semantic web tech to a certain extent.

In Europe, you will run into RDF quite often in academia (and research in general). I'm working on the newest version of the Danish WordNet, for example, which is published as RDF and OWL (in the turtle format) and which runs in Apache Jena. Coincidentally, I am actually developing this new version in Clojure which stole the triplestore concept from the semantic web stack and made it a mainstream database type in the Clojure ecosystem (Datomic, Datascript, Datahike, Datalevin, Asami).