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

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.