INSPIRE Compliant Datasets - Transformation and Conformance Testing
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The INSPIRE initiative sets up a framework for the creation of an European Spatial Data Infrastructure (ESDI), which will enable the sharing of environmental spatial information among public sector organisations and better facilitate public access in general to spatial information across Europe. To do so, several common specifications have been developed in a wide range of areas including data, metadata, and network services. The most challenging aspect of INSPIRE will probably be harmonising the actual data models across Europe to the common INSPIRE ones, giving the amount of time allocated for this process. This task is not only challenging because of the amount of data that will be involved in the process, but also because of the very varied source data models and amount of data providers that will be involved at various stages and having to cooperate at European level under a unique framework. Therefore, the main question that arises, and that is on the mind of many data providers across Europe, is how is that really achieved and what does it involve? This thesis aims to clarify that aspect by focusing on data transformation and conformance testing. The research follows a stepped approach, first of all by putting into the INSPIRE context, concepts like interoperability and data harmonisation, extending to the importance of geographic information standards in this sense, as well as the ultimate goal of a spatial data infrastructure. A case study is considered, where at first, source data from the UK mapping agency, Ordnance Survey, that falls into the scope of one of the INSPIRE thematic themes, namely Administrative Units, is analysed and compared to the target data model proposed by INSPIRE, trying to identify similarities and differences that may pose problems. The process continues with identifying software tools that are capable to perform data transformation based on INSPIRE requirements, and eventually using one of them to transform the data. After the transformation, encountered bottlenecks are discussed, both from the source data side, but also from the target data model side. The last step is to formally test the produced datasets as required by the standards that INSPIRE rely upon, by means of an Abstract Test Suite (ATS) and Executable Test Suite (ETS). This is maybe one of the crucial aspects of INSPIRE data harmonisation process, as there is still some ambiguity between legally binding and not legally binding requirements, an aspect that will directly influence testing and its interpretation, hence the obligations of each data provider. The thesis will conclude with observations that are relevant not only for the Administrative Units theme, but also for the wider scope of INSPIRE data transformation and conformance testing. Main bottlenecks are discussed, but also recommendations are given that would definitely be relevant for further research, as well as for the INSPIRE community.