Bibliometrics Study and Network Analysis of Co-authorship and Thematic Clusters of Ontology Researches

The increasing growth of Ontology Studies in the world has created the need to target scientific research in this field; By using various scientometrics techniques, the status of these studies should be investigated and studied from different points of view. This study aimed to analyze bibliometrics and co-authorship networks, and thematic clusters of ontology studies in the Scopus database during 1996-2020.

This study in terms of purpose is an applied and descriptive scientometrics, which has been done methodologically with co-word analysis and network analysis. The collected data (on December 10, 2020) were analyzed using Excel software. To analyze the data, VOSviewer, Pajek, and UCINet Software were used.

The bibliometric study and analysis of the co-authorship network and thematic clusters of ontology studies in the Scopus database indicates that 0.91% of the articles in this field are written in English and Since 2002, the scientific productions of this field have started their growth period and in 2012, they have reached their growth period. "Expert Systems with Applications" Journal with the publication of 101 articles, the “Journal of Web Semantics” with 80 articles, and “Semantic Web” with 74 articles, are considered the core Journals for the researchers of the Ontology field.  The field of computer science with 3941 articles has the largest share in scientific productions. Zhejiang University with the production of 69 articles (1.32%), Academy of Sciences Research Center and Universidad de Murcia with the production of 68 (1.30%) and 66 articles (1.26%), respectively, are among the most productive research centers in the field of ontology.  R. Valencia-García with 27 articles (0.51%) J.T. Fernández-Breis with 26 articles (0.49%) and M. Dumontier with 23 articles (0.44%) are among the most productive researchers in the field of ontology in the world. the most cooperation in the production of ontology research has been done by the countries of China, the United States, and the United Kingdom. In the study of the co-occurrence network of the Ontology field in the Scopus database, 5 topic clusters were identified which include the semantic web, ontology infrastructure, machine learning, linked data in the data web, and semantic description framework the semantic web cluster is the largest. In terms of the centrality index, Zhang, Y. with a centrality score of 74, Li, J. with a centrality score of 62, and Wang, Y. with a centrality score of 54 are in the first to third ranks. Also, in terms of the closeness centrality index, Stellato, A. with a centrality score of 5640 had the highest degree of closeness. According to the centrality index, Decker, S. with a centrality score of 7037.317, Horrocks, I. with a centrality score of 6686.898, and Wang, Z. with a centrality score of 6217.040 are in a good position in the network. In terms of the centrality index of the special vector, Valencia-García, R. with a centrality score of 1, Garcia Sanchez, F. with a centrality score of 0.868, and Colomo-Palacios, R. with a centrality score of 0.798 were ranked first to third.

Drawing maps of the scientific structure of different disciplines, including ontology, can be useful from different points of view. The analysis of the field of ontology can help researchers to know the scientific limits and boundaries, the general understanding of the scientific structure for beginners, and the choice of the research field, and it can also serve as a guide map for researchers and decision-makers in the field of existence. Science should be used to identify the priorities of research and adapt it to the future needs of society.