Authors:
Sławomir Wójcik
1
;
Taha Osman
2
and
Peter Zawada
1
Affiliations:
1
International Geoscience Services (IGS) Ltd., United Kingdom
;
2
Nottingham Trent University, United Kingdom
Keyword(s):
Geodata, Semantic Web, Geospatial Reasoning, Mineral Prospectivity Analysis.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
Early mineral exploration activities motivates innovative research into cost-effective methods for
automating the process of mineral deposits’ prospectivity analysis. At the heart that process is the
development of a knowledge base that is not only capable of consuming geodata originating from multiple
sources with different representation format and data veracity, but also provides for the reasoning
capabilities required by the prospectivity analysis. In this paper, we present an integrative semantic-driven
approach that reconciles the representation format of sourced geodata using a unifying metadata model, and
encodes the prospectivity analysis of geological knowledge both at the schemata modelling level and
through more explicit reasoning rules operating on the semantically tagged geodata. The paper provides
valuable insights into the challenges of representation, inference, and query of geospatially-tagged
geological data and analyses our initial results into the prospectivity a
nalysis of mineral deposits.
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