Infusing semantics into the knowledge discovery process for the new e-geoscience paradigm
Published:September 01, 2011
A. Krishna Sinha, 2011. "Infusing semantics into the knowledge discovery process for the new e-geoscience paradigm", Societal Challenges and Geoinformatics, A. Krishna Sinha, David Arctur, Ian Jackson, Linda C. Gundersen
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The need to develop a geoscience cyberinfrastructure framework for both the discovery and semantic integration of disciplinary databases in geosciences is abundantly clear as we seek to unravel both the evolutionary history of Earth and address significant societal challenges. Although geoscientists have produced large amounts of data, the ability to find, access, and properly interpret these large data resources has been very limited. The main reason for the difficulties associated with both discovery and integration of heterogeneous and distributed data sets is perhaps related to the adoption of various acronyms, notations, conventions, units, etc., by different research groups. This makes it difficult for other scientists to correctly understand the semantics associated with data, and it makes the interpretation and integration of data simply infeasible. This paper presents the scientific rationale for developing new capabilities for semantic integration of data across geoscience disciplines.
In order to enable the sharing and integration of geosciences data on a global scale, ontology-based data registration and discovery are required. Hence, this paper describes the need to develop foundation-level ontologies for efficient, reliable, and accurate data sharing among geoscientists. Ontologically registered data can be modeled through the use of geoscientific tools to answer complex user queries. This paper emphasizes the need to share tools such as Web services that are registered to a service ontology and made accessible to the scientific community at large. Future development would include an ontology of concepts associated with processes, enabling users to conduct both forward and reverse modeling toward a more robust understanding of complex geoscience phenomena.
This paper presents two use cases for a semantic infrastructure model registering data and services, including processes for analysis of complex geoscience queries.