However, Protege is a modeling tool not a database. So when you start getting into large amounts of data (e.g., 10K instances or more) you will need another tool, ideally a database. There are tools to do what's called Data Virtualization, where you can represent your data (what OWL users call the A-Box, i.e., the equivalent of instances in OOP or rows in a relational DB) in a relational database and map the data... Source: over 1 year ago

Along those lines, not Jena but useful for playing with ideas is Protege, Https://protege.stanford.edu/. Source: about 1 year ago

If you go with the Semantic Web there are many tools. The best free tool (possibly the best tool period) for creating OWL ontologies is the Protege ontology editor developed at Stanford. I wrote a tutorial that explains how to use Protege and gives more detail on OWL, SPARQL, etc. https://www.michaeldebellis.com/post/new-protege-pizza-tutorial. Source: over 1 year ago

The case is different for more mature ontologies. The prime example is the sharing of drug information among drug vendors. They have an incentive to share because that ultimate saves them time in developing a drug that may already have been developed. It's like a prescreening for patenable drugs. They sgare knowledge in an ontology library called "Bioportal". Many of the dntris are written in a form suported by... Source: almost 2 years ago

If you could put this into an ontological solver format, like Cyc or protege ( https://protege.stanford.edu/ ) then create a couple dozen translations of real laws into the format, you could turn gpt-3 loose on the entire set of United States federal, state, and local laws and regulations. Then propose a question to the solver using your model whereby a person can successfully sue or acquire property according to... - Source: Hacker News / over 2 years ago