Semantic Interoperability through the Definition of Conceptual Model Transformations

TLDR

Integrating distributed geospatial data across heterogeneous systems and borders remains a major challenge in geoinformatics. The study proposes a four‑step, model‑based approach to conceptual data modelling that maps data models conceptually without altering data formats. The authors developed UMLT, a conceptual mapping language integrated into Model‑Driven Architecture, which automatically derives data‑format transformations from platform‑independent to platform‑specific models. The approach, combined with attribute‑mapping operations, achieves effective and enhanced semantic interoperability.

Abstract

Abstract The integration of distributed geospatial data is a great issue in GI Science. Hereby, the collection of data from different systems and different structures as well as across country borders is a problem. We explain a model‐based four‐step approach to conceptual data modelling. Within this approach, we introduce a methodology to map data models on the conceptual level without touching data formats. First, we developed a conceptual mapping language called “UMLT” which is the core of our approach. Furthermore, we integrated UMLT into the Model‐Driven Architecture where a conceptual model mapping is referred to as a platform independent model mapping. Finally, the data format transformation is deduced from the model mapping automatically. This represents the implementation mapping from a platform independent model to a platform specific model. Together with transformation operations for attribute mapping, this approach is a means for effective and enhanced semantic interoperability.