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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

The Open Geospatial Consortium (OGC) is an international non-profit standards organization. Established in 1994, OGC aims to make geospatial information and services FAIR-Findable, Accessible, Interoperable, and Reusable. OGC specifications have greatly facilitated interoperability among software, hardware, data, and users in the GIS field. This study collected publications related to OGC specifications from the Web of Science (WoS database) between 1994 to 2020 and conducted a literature analysis using Derwent Data Analyzer and VosViewer, finding that OGC specifications have been widely applied in academic fields. The most productive organizations were Wuhan University and George Mason University; the most common keywords were interoperability, data, and web service. Since 2018, the emerging keywords that have attracted much attention from researchers were 3D city models, 3D modeling, and smart cities. To make geospatial data FAIR, the OGC specifications SWE and WMS served more for “Findable”, SWE contributed more to “Accessible”, WPS and WCS served more for “Interoperable”, and WPS, XML schemas, WFS, and WMS served more for “Reusable”. The OGC specification also serves data and web services for large-scale infrastructure such as the Digital Earth Platform of the Chinese Academy of Sciences.

Details

Title
Bibliometric Analysis of OGC Specifications between 1994 and 2020 Based on Web of Science (WoS)
Author
Huang, Mingrui 1   VIAFID ORCID Logo  ; Fan, Xiangtao 2 ; Hongdeng Jian 2 ; Zhang, Hongyue 3 ; Guo, Liying 4   VIAFID ORCID Logo  ; Di, Liping 4 

 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), Beijing 100094, China; [email protected] (M.H.); [email protected] (X.F.); [email protected] (H.J.); University of Chinese Academy of Sciences (UCAS), No.19 Yuquan Road, Shijingshan District, Beijing 100049, China; International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, China; Center for Spatial Information Science and Systems (CSISS), George Mason University, Fairfax, VA 22030, USA; [email protected] 
 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), Beijing 100094, China; [email protected] (M.H.); [email protected] (X.F.); [email protected] (H.J.); International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, China 
 Ocean College, Minjiang University, Fuzhou 350108, China; [email protected] 
 Center for Spatial Information Science and Systems (CSISS), George Mason University, Fairfax, VA 22030, USA; [email protected] 
First page
251
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
22209964
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2652979653
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.