Ontotext is a commercial company that since 2000 helps enterprises identify meaning across diverse datasets and massive amounts of unstructured information since 2000. The vision behind their technology is to enable machines to interpret data and text, which empowers our customers to reveal more facts and relationships quickly and with less effort. By interlinking data in graphs that model knowledge as it is represented in the human’s brain, we enable enterprises not only to access this knowledge, but also to interpret and analyze it. It is then possible to link this data with text by generating metadata that also becomes part of the knowledge graph allowing even more complex analytics and querying of hidden information. Finally, Ontotext integrates open data with proprietary data and commercial databases to make use of the exponentially growing web of open data.
Role in the project
- Technical architecture for semantic harmonization level,
- development of semantic model,
- automatic information extraction,
- missing data imputation,
- European Open Stroke Data Platform establishment,
- work package 3 leader.
RES-Q+ WP 3 Leader
NLP and automatic data extraction tool lead
Semantic Layer Solution Architect