Automatic annotation and classification of texts are often performed using machine learning techniques, statistical methods, controlled vocabularies and ontologies (e.g. SKOS), or comprehensive knowledge graphs such as DBpedia or Wikidata.
All these methods have advantages and disadvantages as discussed and summarized in this presentation. But what if all these methods are combined? What new possibilities for text analysis arise from this, and how does this influence the governance model underlying the knowledge modeling process?
The difficulty of representing and organizing knowledge, especially in reasonably complete and not “implicitly redundant” ways, raises at least two research questions: “how to check that certain relations are systematically used not simply whenever this is possible but whenever this is relevant for the knowledge providers?” and “how to extend best practices, ontology patterns or methodologies that advocate the systematic use of certain relations, and make the following of these methods easier to check?”.
In this presentation we want to showcase the introduction of our
Semantic Web powered software development platform, modom.io at WSCAD,
Germany’s most innovative E-CAD solution provider.
We will present our achievements for improving knowledge management in software engineering and share how we used ontologies and Linked Data to reach these goals. At the end of the talk there will be a live
demo of modom.io and an outlook into future developments.