Multilingual Knowledge Systems as Linguistic Linked Open Data
Alena Vasilevich, Michael Wetzel · Cognitive technologies · 2022
Abstract Creation and re-usability of language resources in accordance with Linked Data principles is a valuable asset in the modern data world. We describe the contributions made to extend the Linguistic Linked Open Data (LLOD) stack with a new resource, Coreon MKS, bringing together concept-oriented, language-agnostic terminology management and graph-based knowledge organisation. We dwell on our approach to mirroring of Coreon’s original data structure to RDF and supplying it with a SPARQL endpoint. We integrate MKS into the existing ELG infrastructure, using it as a platform for making the published MKS discoverable and retrievable via a industry-standard interface. While we apply this approach to LLOD-ify Coreon MKS, it can also provide relevant input for standardisation bodies and interoperability communities, acting as a blueprint for similar integration activities.