A Review of the Semantic Web Field
We built a new semantic database first in university and then commercial open source (TerminusDB). We use the web ontology language (OWL) as a schema language, but made two important - practical - modifications: 1) we dispense with the open world interpretation; and 2) insist on the unique name assumption. This provides us with a rich modelling language which delivers constraints on the shapes in the graph. Additionally, we don&#x27;t use SPARQL, which we didn&#x27;t find practical (composability is important to us) and use a Datalog in its place (like Dataomic and others).<p>Our feeling on interacting with the semantic web community is that innovation - especially when it conflicts with core ideology - is not welcome. We understand that &#x27;open world&#x27; is crucial to the idea of a complete &#x27;semantic web&#x27;, but it is insanely impractical for data practitioners (we want to know what is in our DB!). Semantic web folk can treat alternative approaches as heresy and that is not a good basis for growth.<p>As we came from university, I agree with comments that the field is too academic and bends to the strange incentives of paper publishing. Lots of big ideas and everything else is mere &#x27;implementation detail&#x27; - when, in truth, the innovation is in the implementation details.<p>There are great ideas in the semantic web, and they should be more widespread. Data engineers, data scientists, and everybody else can benefit, but we must extract the good and remove ideological barriers to participation.