Summary and Conclusions

The goal of this document is to summarize what was done in this project and to describe how it was done, so that partners in the DRDSI can continue to create their own harmonized data sets and publish them as INSPIRE-compliant download and view services.

The general methodology that we applied was similar to the common INSPIRE data harmonisation methodology:

1. Identify the INSPIRE thematic scope of each available data set;
2. Analyse the quality of source data sets with respect to meeting the minimum requirements of the identified INSPIRE thematic scope, focused on completeness, conformity, and consistency (see Deliverable D1)
3. Determine which types, class or tables in the source data have to be mapped to which target types, then determine which properties or sub-elements have to be mapped to which target properties (see Deliverable D2)
4. Transform and Validate Data Sets using hale studio and the Epsilon INSPIRE Cloud validation service (see Deliverable D3)
5. Publish Data Sets as services and validate service and dataset metadata (see Deliverable D4)

For detailed descriptions of each of these steps, please refer to the other deliverables. A complete description is also available at http://inspire-extensions.wetransform.to.

Conclusions and Open Points

With relatively simple source models, performing the analysis and harmonisation of the source data sets was not problematic. The main issue was missing stable identifiers, as well as a general lack of thematic depth – the data provided was sufficient to do minimum INSPIRE data sets, but was not enough to go far beyond that.

We think it would make sense to include as much of the generated resources as possible with the DRDSI and AR3ENA platforms to make the project results more accessible. It should also be clarified whether services and other created resources should be published officially or not.