A bibliometric and visual analysis of global geo-ontology research
A bibliometric and visual analysis of global geo-ontology research
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DOI：
10.1016/j.cageo.2016.10.006
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发表时间：
2017-02-01
影响因子：
4.4
通讯作者：
Shen, Hang
中科院分区：
文献类型：
--
作者：
Li, Lin;Liu, Yu;Shen, Hang
In this paper, the results of a bibliometric and visual analysis of geo-ontology research articles collected from the Web of Science (WOS) database between 1999 and 2014 are presented. The numbers of national institutions and published papers are visualized and a global research heat map is drawn, illustrating an overview of global geo-ontology research. In addition, we present a chord diagram of countries and perform a visual cluster analysis of a knowledge co-citation network of references, disclosing potential academic communities and identifying key points, main research areas, and future research trends. The International Journal of Geographical Information Science, Progress in Human Geography, and Computers & Geosciences are the most active journals. The USA makes the largest contributions to geo-ontology research by virtue of its highest numbers of independent and collaborative papers, and its dominance was also confirmed in the country chord diagram. The majority of institutions are in the USA, Western Europe, and Eastern Asia. Wuhan University, University of Munster, and the Chinese Academy of Sciences are notable geo-ontology institutions. Keywords such as "Semantic Web," "GIS," and "space" have attracted a great deal of attention. "Semantic granularity in ontology-driven geographic information systems, "Ontologies in support of activities in geographical space" and "A translation approach to portable ontology specifications" have the highest cited centrality. Geographical space, computer-human interaction, and ontology cognition are the three main research areas of geo-ontology. The semantic mismatch between the producers and users of ontology data as well as error propagation in interdisciplinary and cross-linguistic data reuse needs to be solved. In addition, the development of geoontology modeling primitives based on OWL (Web Ontology Language) and finding methods to automatically rework data in Semantic Web are needed. Furthermore, the topological relations between geographical entities still require further study.
