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These days many data providers implement INSPIRE data harmonization at the end of the data pipeline. The harmonized data is hardly used by the organisations itself. This approach has a big risk. In the harmonization process, data may get lost or be placed out of context. That's why, for those situations, I'm suggesting an alternative light weighted harmonization approach based on linked data principles.
The idea for this approach started in the Geo-for-the-web testbed of Geonovum and the INSPIRE what-if sessions at the OGC meeting in Delft. It was extended and implemented in customer projects and presented at the INSPIRE Hackathon in Orleans.
The idea of the approach is to extend feature catalog metadata (iso19110) of INSPIRE as-is datasets with references to relevant INSPIRE ontologies (https://github.com/inspire-eu-rdf/inspire-rdf-vocabularies) in such a way that client software (like http://www.ldproxy.net) would be able to take the as-is dataset combined with the extended iso19110 metadata to create INSPIRE RDF triples, which then could be transformed into GML.
The first implementations with the extended feature catalog metadata are currently operational at various Dutch provinces and water boards. In next iterations I would like to look at conversion mechanisms for the triples. Join us in the INSPIRE hackathons if you have an interest in this topic.
Topic Area: [3.2] Tools and technologies Abstract Type: Oral Presentation
Academic: Yes Data Provider: Yes Data User: No INSPIRE Implementer (IT): Yes INSPIRE newbies: No Policy Officers: No Public Administration (MS/Regional/Local): Yes Thematic specialists: No
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