SEMANTICALLY-ENABLED E-GEOSCIENCE FOR KNOWLEDGE DISCOVERY

Geoscientists are seeking new knowledge related to studies of climate change, planetary processes, natural resources and hazards. As the complexities of these processes are only recently being recognized, it is evident that an enormous gain in understanding can be realized only if multidisciplinary heterogeneous data are discovered and integrated through geoinformatics. The current methods of data discovery involve URL lookups, or accessing targeted data sets, thereby defeating the very purpose of conducting multidisciplinary science. The problem is exacerbated in cases of syntactic and semantic data differences. In terms of data management, semantics refers to the information about what the data is or contains while syntax specifies the format of the data. Although both are required for interoperability, semantic management of data allows for inter-disciplinary integration not possible through syntactic procedures. Several initiatives aimed at syntactic interoperability have resulted in the development of “markup languages” (in XML format) for disciplines such as geological maps (e.g. One Geology), hydrology, images, etc. However, to enable machines to automatically understand and process data with minimal human intervention, data needs to be empowered with semantic annotations. This would reduce the current laborious and error-prone data discovery and integration performed by the user. To enable discovery and integration of data, tools and services, we are developing a semantic framework for the geosciences. Ontologies are central to this approach as they provide an organizational structure for rapid discovery of data, tools and services leading to integration in a Web environment. We have built a prototype Discovery, Integration, and Analysis (DIA) engine that uses the ontologically (semantic) registered data to create previously unknown knowledge (data products). Geoscientists thus only focus on the solution of a problem, while the processes involved in data discovery and integration work in the background. Since DIA requires semantic registration of data and services, we are developing a Semantics-Enabled Data Registration Engine (SEDRE) for the geoscience community. This semantically enabled integrative capability will facilitate the conduct of e-geoscience in the 21st century.