Who is using Semantic Web technology in production?
Semantic Web movement has produced several technologies (JSON-LD, SPARQL, OWL, etc) that seem useful for data integration, but they don't appear to have much momentum. I'm struggling to determine if the Semantic Web is a justly abandoned bad idea or a quietly useful mature technology.
The main place I see Semantic Web technology in use is SEO [1] and Email Markup [2]. Is anyone using these technologies for more general data integration tasks?
[1] https://www.bing.com/webmaster/help/markup-validator-e9b66817
[2] https://developers.google.com/gmail/markup/getting-started
5 comments
[ 3.2 ms ] story [ 27.0 ms ] threadhttp://ontology2.com/the-book/rdf-a-new-slant.html
JSON-LD and SPARQL are fine, OWL as an inference system has some good ideas (implementable by macros on top of production rules) but it is not adequate to do what people need for data integration (multiply, divide, add, subtract for one thing.)
I like the idea of using RDF as a universal data model. I buy the power of graphs in general, and RDF seems much more useful than a generic object-property graph thanks to built in support for namespaces and reasoners.
My hesitation about the concept comes from concerns around performance and implementation difficulty. It looks like you've built some solid tools to ease the initial modelling challenge, how are you addressing the performance challenges? That is, once you pull several data sources into a huge graph, how do you keep query speed up?
Trying to get the whole world inside one "envelope" is scalability pornography, i.e. SAP HANA.
Realistically you create the indexes and data structures necessary for your workload, it is not that different from any other technology except in the case of RDF the math is known.
DBopedia and other serious projects offer endpoints. And the nature of the format means one can federate queries across them . DBopedia is currently the defacto ontology/ starting point.