Framework para integração semântica de dados geoespaciais: integração de dados geológicos - Antonialli, Rodrigo Cesar [UNESP] (2015)
Data integration is a constant need in researches and work in Geology, part of Geosciences responsible for studying several characteristics of Earth. This need comes from the fact that data are usually produced by different organizations and/or research groups, which may study large areas and/or relate different subjects associated with Geology within these studies. The decentralized information production cause the data to be described with different schemas and different interpretations of the concepts related to them. The volume of data that can be generated in Geological studies brings the need to automate the integration process. However, traditional approaches based on syntactic comparison of data schema may not be enough to perform the task. Geological data have complex characteristics which rely on conceptual aspects to be analyzed. Thus, geological data integration a more complete level of information representation approach, that considers the concepts related to the data. Within the presented context, the Framework for Geospatial Semantic Integration proposed in this work aims to integrate geological data based on ontologies, and to consider the fundamental geospatial characteristics of these data. However, the ontologies that describe concepts related to Geology may be defined with different interpretations of these concepts relations. To overcome this semantic heterogeneity, the proposed framework uses the ontology alignment process. The framework also considers geological data availability aspects, which may vary as public, with free access and sharing possibilities or as restricted, with controlled access, mainly when the data is about strategic activities, as mineral and energetic resources exploration. In the integration process proposed in the framework, a semantic analysis of the data is executed; based on rules, it identifies cases of duplications, conflicts or combinations of geological data