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 proceedingConference proceedingpeer-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 languageEnglish
Title of host publicationPattern Analysis, Intelligent Security and the Internet of Things
EditorsAjith Abraham, Azah Kamilah Muda, Yun-Huoy Choo
PublisherSpringer-Verlag Wien
Pages35-47
Number of pages13
ISBN (Electronic)9783319173986
ISBN (Print)9783319173979
DOIs
Publication statusPublished - 21 Jun 2015
Externally publishedYes
Event4th World Congress on Information and Communication Technologies, WICT 2014 - Malacca, Malaysia
Duration: 8 Dec 201411 Dec 2014

Publication series

NameAdvances in Intelligent Systems and Computing
Volume355
ISSN (Print)2194-5357

Conference

Conference4th World Congress on Information and Communication Technologies, WICT 2014
Country/TerritoryMalaysia
CityMalacca
Period8/12/1411/12/14

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
  • Computer Science(all)

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