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Frequency Statistics Dataset on Geographic Scenario based on Scopus and CNKI (2020-2023)


JING Changfeng1,2LI Jianing1WU Sensen3FENG Yunlong1CAO Yibing4CHEN Yijun3JIANG Jie1ZHOU Chenghu5
1 School of Geomatics and Urban Spatial Informatics,Beijing University of Civil Engineering and Architecture,Beijing 100044,China2 School of Information Engineering,China University of Geosciences,Beijing 100083,China3 School of Earth Sciences,Zhejiang University,Hangzhou 310027,China4 Institute of Geo-spatial Information,Information Engineering University,Zhengzhou 450052,China5 State Key Laboratory of Resources and Environment Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China

DOI:10.3974/geodb.2024.11.07.V1

Published:Nov. 2024

Visitors:10       Data Files Downloaded:0      
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Key Words:

Geographic Scenario,Scopus,CNKI,2000-2023

Abstract:

The Frequency Statistics Dataset on Geographic Scenario based on Scopus and CNKI (2020-2023) was developed with statistics on the number of papers, authors, and related institutions. The dataset includes the following data from 2000 to 2023: (1) the number of papers published on the topic of "Geographic Scenario" in Scopus; (2) the annual publication data of the top 15 authors focusing on "Geographic Scenario" topic; (3) the distribution of the top 10 author institution of "Geographic Scenario" topic; (4) the distribution of the "Geographic Scenario" topic from CNKI. The dataset was archived in .xlsx format, and consists of one data file with data size of 13.8 KB. The analysis article based on this dataset was published in Acta Geographica Sinica, Vol. 79, No. 9, 2024.

Foundation Item:

Ministry of Science and Technology of P. R. China (2021YFB3900902)

Data Citation:

JING Changfeng, LI Jianing, WU Sensen, FENG Yunlong, CAO Yibing, CHEN Yijun, JIANG Jie, ZHOU Chenghu.Frequency Statistics Dataset on Geographic Scenario based on Scopus and CNKI (2020-2023)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.11.07.V1.

References:

[1] https://www.scopus.com/.
     [2] https://www.cnki.net/.
     

Data Product:

ID Data Name Data Size Operation
1 Sta_GeoScenario.xlsx 13.81KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum