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SeaDataCloud is a four year Horizon 2020 project, which started in November 2016. The project continues the 20 year long endeavor of the SeaDataNet network to develop a Marine Spatial Data Infrastructure for data providers and users in the marine domain. The present SeaDataCloud project strives, among other things, to improve the INSPIRE compliance of the data collected and maintained by SeaDataNet.
In 2017 the first steps towards INSPIRE compliance were made: this work started off with a review of the INSPIRE data models of relevance to the SeaDataNet community, the INSPIRE Themes Oceanographic Features (OF), Environmental Monitoring Facilities (EF) as well as the Observational Model provided within the INSPIRE Generic Conceptual Framework (GCM) where identified as relevant to SeaDataNet data. Once the relevant INSPIRE Themes and classes were identified, an alignment of concepts required by the INSPIRE regulations as well as those stemming from SeaDataNet was undertaken; the alignment was documented in a spreadsheet describing the correspondences between the SeaDataNet data and metadata formats and relevant INSPIRE application schemas. Once the alignment process was completed, sample XML/GML files were created to illustrate how how SeaDataNet data can be provided in an INSPIRE compliant manner.
In our presentation we will present the work done, issues encountered and the recommendations for future topics for the INSPIRE and SeaDataNet communities.
The results of the SeaDataCloud project have already been re-used in the TG-DATA group, when outlining the guidelines for the usage of INSPIRE in the Marine Strategy Framework Directive reporting. However the details of this work will not be covered in this presentation.
Topic Area: [2.2] International cooperation at EU/EFTA/EEA level Abstract Type: Oral Presentation
Academic: Yes Data Provider: Yes Data User: Yes INSPIRE Implementer (IT): Yes INSPIRE newbies: No Policy Officers: Yes Public Administration (MS/Regional/Local): Yes Thematic specialists: Yes Comments: SeaDataNet, INSPIRE, OF, EF, O&M, encoding, data model
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