NIF4OGGD - NLP Interchange Format for Open German Governmental Data
Mohamed Sherif, S Coelho, ro, Ricardo Usbeck, Sebastian Hellmann, Jens Lehmann, Martin Br{\"u}mmer, Andreas Both
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In the last couple of years the amount of structured open government data has increased significantly. Already now, citizens are able to leverage the advantages of open data through increased transparency and better opportunities to take part in governmental decision making processes. Our approach increases the interoperability of existing but distributed open governmental datasets by converting them to the RDF-based NLP Interchange Format (NIF). Furthermore, we integrate the converted data into a geodata store and present a user interface for querying this data via a keyword-based search. The language resource generated in this project is publicly available for download and also via a dedicated SPARQL endpoint.