Extracting Enterprise Vocabularies Using Linked Open Data A common vocabulary is vital to smooth business operation, yet codifying and maintaining an enterprise vocabulary is an arduous, manual task. We describe a process to automatically extract a domain specific vocabulary (terms and types) from unstructured data in the en- terprise guided by term definitions in Linked Open Data (LOD). We validate our techniques by applying them to the IT (Information Tech- nology) domain, taking 58 Gartner analyst reports and using two specific LOD sources – DBpedia and Freebase. We show initial findings that ad- dress the generalizability of these techniques for vocabulary extraction in new domains, such as the energy industry.
IBM Watson Research Center
alphaWorks : IBM Web Ontology Manager IBM Web Ontology Manager is a lightweight, Web-based tool for managing ontologies expressed in Web Ontology Language (OWL). With this technology, users can browse, search, and submit ontologies to an ontology repository. This technology includes a Web interface for easy uploading of ontologies in an .owl format by any user of the system. It also includes an interface for generating (using Jastor) Java™ APIs from uploaded ontology files.
IBM Web Ontology Manager differs from IBM Ontology Management System (a former alphaWorks technology, now merged into the IBM Integrated Ontology Development Toolkit) in that it does not include a statement repository. Instead, based on the ontologies visible to the system, it can generate Java classes for accessing any Jena-compatible RDF statement repository.