Semantic Search System for Research Data in Information Science
DOI:
https://doi.org/10.14456/iskku.2021.15Keywords:
Research data, Research article, Information science, Ontology, Semantic searchAbstract
Purpose of the study: This investigation aimed at developing ontology and semantic search system for research data in information science using the topic modeling method.
Methodology: This research and development study analyzed and classified 30,571 research articles published in internal journals and indexed by Web of Science Database from 2013 to 2019. After the ontology and semantic search system had been developed, they were evaluated by experts and system users, and the assessed data were statistically analyzed.
Findings: The ontology comprised 3 main classes: 1) research articles and 2) research topics with 30 subclasses each, and 3) research category which was accompanied by only 2 subclasses. These 3 main classes provided properties, relations and descriptions. The analysis of the assessment of the ontology quality by the experts revealed that its quality and effectiveness as a whole was at the very high level, and the semantic search system for retrieving research data in information science could be conducted through the use of the properties, research topics and category.
Applications of the study: The ontology for research data in information science is of useful direction for determining research trends in information science, and the semantic search system can be used as a guideline for developing research data in other subject fields.
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