An ontological approach for knowledge modeling and reasoning over heterogeneous crop data sources

Rakib, Abdur; Lawan, Abba; Walker, Sue

Abstract

© Springer International Publishing Switzerland 2015. The past two decades have seen a remarkable shift in the knowledge-and information-sharing paradigm. In the crops domain, for example, the amount of information currently known about underutilized crops, for example, Bambara groundnut their genetics and agronomy are much richer than years before. That paradigm shift offers enormous potential for advancing knowledge representation systems to facilitate access to such data. However, inconsistencies in terminology, improper syntax, and semantics are main obstacles to sharing data and knowledge among disparate researchers. We present a formal framework for representing knowledge using OWL 2 RL ontologies and SWRL rules and to integrate and reason over data from multiple, heterogeneous underutilized crops data sources.

Citation

Rakib, A., Lawan, A., & Walker, S. (2015). An ontological approach for knowledge modeling and reasoning over heterogeneous crop data sources. Advances in Intelligent Systems and Computing, 355, 35-47. https://doi.org/10.1007/978-3-319-17398-6_4

• Journal Article Type: Conference Paper
• Publication Date: Jan 1, 2015
• Deposit Date: Jun 16, 2017
• Journal: Advances in Intelligent Systems and Computing
• Print ISSN: 2194-5357
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 355
• Pages: 35-47
• Series Title: Advances in Intelligent Systems and Computing
• Series Number: 1
• Book Title: Pattern Analysis, Intelligent Security and the Internet of Things
• ISBN: 9783319173979
• DOI: https://doi.org/10.1007/978-3-319-17398-6_4
• Keywords: ontology, heterogeneity, knowledge representation, reasoning, semantic web rule language
• Public URL: https://uwe-repository.worktribe.com/output/832598
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-17398-6_4