Spatial Data Infrastructures (SDIs) aim at making spatial (geographical) data and thus content available for the benefit of the economy and of the society. Agreement and sharing of vocabularies within the SDI are vital for interoperability. But there is a limitation: many vocabularies have been defined within domains while other domains have not been taken into account. Therefore, little harmonisation has been achieved and data sharing between domains within the SDI is problematic. This paper presents a methodology and tools for non-automatic, community driven ontology matching that we developed to harmonise the definition of concepts in domain models that are already being defined and used in operational use cases. Besides the methodology and tools that we developed, we describe our experiences and lessons learned as well as future work.
|Journal||Computers, Environment and Urban Systems|
|Publication status||Published - 2017|
- Semantic harmonisation
- Spatial data infrastructure
- Ontology matching
- Community driven