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

Abdur Rakib; Abba Lawan; Sue Walker

doi:10.1007/978-3-319-17398-6_4

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

Abdur Rakib
, Abba Lawan
, Sue Walker

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Pattern Analysis, Intelligent Security and the Internet of Things
Editors	Ajith Abraham, Azah Kamilah Muda, Yun-Huoy Choo
Publisher	Springer-Verlag Wien
Pages	35-47
Number of pages	13
ISBN (Electronic)	9783319173986
ISBN (Print)	9783319173979
DOIs	https://doi.org/10.1007/978-3-319-17398-6_4
Publication status	Published - 21 Jun 2015
Externally published	Yes
Event	4th World Congress on Information and Communication Technologies, WICT 2014 - Malacca, Malaysia Duration: 8 Dec 2014 → 11 Dec 2014

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	355
ISSN (Print)	2194-5357

Conference

Conference	4th World Congress on Information and Communication Technologies, WICT 2014
Country/Territory	Malaysia
City	Malacca
Period	8/12/14 → 11/12/14

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Keywords

Heterogeneity
Knowledge representation
Ontology
Reasoning
Semantic Web rule language

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-319-17398-6_4

Cite this

Rakib, A., Lawan, A., & Walker, S. (2015). An ontological approach for knowledge modeling and reasoning over heterogeneous crop data sources. In A. Abraham, A. K. Muda, & Y.-H. Choo (Eds.), Pattern Analysis, Intelligent Security and the Internet of Things (pp. 35-47). (Advances in Intelligent Systems and Computing; Vol. 355). Springer-Verlag Wien. https://doi.org/10.1007/978-3-319-17398-6_4

An ontological approach for knowledge modeling and reasoning over heterogeneous crop data sources. / Rakib, Abdur; Lawan, Abba; Walker, Sue.
Pattern Analysis, Intelligent Security and the Internet of Things. ed. / Ajith Abraham; Azah Kamilah Muda; Yun-Huoy Choo. Springer-Verlag Wien, 2015. p. 35-47 (Advances in Intelligent Systems and Computing; Vol. 355).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Rakib, A, Lawan, A & Walker, S 2015, An ontological approach for knowledge modeling and reasoning over heterogeneous crop data sources. in A Abraham, AK Muda & Y-H Choo (eds), Pattern Analysis, Intelligent Security and the Internet of Things. Advances in Intelligent Systems and Computing, vol. 355, Springer-Verlag Wien, pp. 35-47, 4th World Congress on Information and Communication Technologies, WICT 2014, Malacca, Malaysia, 8/12/14. https://doi.org/10.1007/978-3-319-17398-6_4

Rakib A, Lawan A, Walker S. An ontological approach for knowledge modeling and reasoning over heterogeneous crop data sources. In Abraham A, Muda AK, Choo YH, editors, Pattern Analysis, Intelligent Security and the Internet of Things. Springer-Verlag Wien. 2015. p. 35-47. (Advances in Intelligent Systems and Computing). Epub 2015 Jan 1. doi: 10.1007/978-3-319-17398-6_4

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this