Development of ontology from Indian agricultural e-governance data using IndoWordNet: a semantic web approach

Abstract

Purpose – The purpose of this explorative research study is to focus on the implementation of semantic Web technology on agriculture domain of e-governance data. The study contributes to an understanding of problems and difficulties in implantations of unstructured and unformatted unique datasets of multilingual local language-based electronic dictionary (IndoWordnet). Design/methodology/approach – An approach to an implementation in the perspective of conceptual logical concept to realization of agriculture-based terms and terminology extracted from linked multilingual IndoWordNet while maintaining the support and specification of the World Wide Web Consortium (W3C) standard of semantic Web technology to generate ontology and uniform unicode structured datasets. Findings – The findings reveal the fact about partial support of extraction of terms, relations and concepts while linking to IndoWordNet, resulting in the form of SynSets, lexical relations of Words and relations between themselves. This helped in generation of ontology, hierarchical modeling and creation of structured metadata datasets. Research limitations/implications – IndoWordNet has limitations, as it is not fully revised version due to diversified cultural base in India, and the new version is yet to be released in due time span. As mentioned in Section 5, implications of these ideas and experiments will have good impact in doing more exploration and better applications using such wordnet. Practical implications – Language developer tools and frameworks have been used to get tagged annotated raw data processed and get intermediate results, which provides as a source for the generation of ontology and dynamic metadata. Social implications – The results are expected to be applied for other e-governance applications. Better use of applications in social and government departments. Originality/value – The authors have worked out experimental facts and raw information source datasets, revealing satisfactory results such as SynSets, sensecount, semantic and lexical relations, class concepts hierarchy and other related output, which helped in developing ontology of domain interest and, hence, creation of a dynamic metadata which can be globally used to facilitate various applications support.