The SmartOpenData project was funded under the Call ENV.2013.6.5‐3 “Exploiting the European Open Data Strategy to mobilise the use of environmental data and information” and it has been carried out with the conviction that opening up public sector data and information for re‐use has a significant potential to act as an engine for innovation, growth and transparent governance. This was the original vision of the project and its results have proved that exploiting Europe's Open Data Strategy contribute to decision‐making in policy areas, fostering the participation of citizens in environmental governance and generating new innovative products and services.
Using open, readily accessible and freely available Earth Observation data and information as the main original datasources, although SmartOpendata has gone further in some specific cases, by publishing datasets that are not completely public or freely available for Citizenship, the SmartOpenData project has enabled wide access to scientific data using Linked Open Data paradigms and Semantic Web tools.
Therefore, SmartOpenData has discovered, transformed and published several biodiversity and environmental data sources. The datasets to be used were requested (if they were not open) and collected. In some cases, they were completely transformed before publication. Publishing those datasets facilitated full access to this useful information for SMEs, general citizenship, policy makers and other relevant stakeholders.
The analysis of Semantic Technologies allowed the project to understand and disseminate the Linked Open Data ‐LOD‐ Technologies inside the geospatial community. Besides this, the dialogue has been enriching in both directions. Indeed, the general principles of geographic information systems and geospatial data were also explained to technical partners, that now know better the natural, environmental and biodiversity contexts.
This approach has allowed researchers in different domains, especially GIS and Data Modelling and Processing, to collaborate on the same data sets, to ensure seamless interoperability of data catalogues, to engage in entirely new forms of scientific research and to explore correlations between research results.