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Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province

The knowledge graph based on research papers can accurately identify and present the latest developments in scientific and technological (S&T) innovation and is of great significance for supporting strategic decision-making relating to S&T innovation in undeveloped areas. Based on the intern...

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Detalles Bibliográficos
Autores principales: Liu, Wenhao, Shi, Xiaoqian, Zheng, Junwei, Li, Ren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019399/
https://www.ncbi.nlm.nih.gov/pubmed/37363035
http://dx.doi.org/10.1007/s10668-023-03124-0
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author Liu, Wenhao
Shi, Xiaoqian
Zheng, Junwei
Li, Ren
author_facet Liu, Wenhao
Shi, Xiaoqian
Zheng, Junwei
Li, Ren
author_sort Liu, Wenhao
collection PubMed
description The knowledge graph based on research papers can accurately identify and present the latest developments in scientific and technological (S&T) innovation and is of great significance for supporting strategic decision-making relating to S&T innovation in undeveloped areas. Based on the international research papers produced in Gansu Province during the 13th Five-Year Plan period (2016–2020), five metrics, including the number and characteristics of papers, co-authors, main publications and their fields, major supporting institutions, and main research areas, are established herein. The results indicate that: (i) the total of 29,951 papers were published, which is about 2.89 times that in 2010–2015; (ii) Gansu Province collaborated with 149 countries/regions globally; (iii) the top 5 journals in terms of the number of papers were Medicine, Scientific Reports, RSC Advances, Science of the Total Environment, and Physical Reviews D; (iv) the funding sources were mainly from the national level; and (5) the top 5 research areas were chemistry, engineering, physics, material science, environmental science, and ecology, which accounted for 64.7% of all papers. Finally, the present study puts forward some recommendations for the decision-making process in the strategic layout of S&T innovation in Gansu Province.
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spelling pubmed-100193992023-03-16 Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province Liu, Wenhao Shi, Xiaoqian Zheng, Junwei Li, Ren Environ Dev Sustain Case Study The knowledge graph based on research papers can accurately identify and present the latest developments in scientific and technological (S&T) innovation and is of great significance for supporting strategic decision-making relating to S&T innovation in undeveloped areas. Based on the international research papers produced in Gansu Province during the 13th Five-Year Plan period (2016–2020), five metrics, including the number and characteristics of papers, co-authors, main publications and their fields, major supporting institutions, and main research areas, are established herein. The results indicate that: (i) the total of 29,951 papers were published, which is about 2.89 times that in 2010–2015; (ii) Gansu Province collaborated with 149 countries/regions globally; (iii) the top 5 journals in terms of the number of papers were Medicine, Scientific Reports, RSC Advances, Science of the Total Environment, and Physical Reviews D; (iv) the funding sources were mainly from the national level; and (5) the top 5 research areas were chemistry, engineering, physics, material science, environmental science, and ecology, which accounted for 64.7% of all papers. Finally, the present study puts forward some recommendations for the decision-making process in the strategic layout of S&T innovation in Gansu Province. Springer Netherlands 2023-03-16 /pmc/articles/PMC10019399/ /pubmed/37363035 http://dx.doi.org/10.1007/s10668-023-03124-0 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Case Study
Liu, Wenhao
Shi, Xiaoqian
Zheng, Junwei
Li, Ren
Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province
title Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province
title_full Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province
title_fullStr Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province
title_full_unstemmed Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province
title_short Characteristics of the knowledge graph of scientific and technological innovation in Gansu Province
title_sort characteristics of the knowledge graph of scientific and technological innovation in gansu province
topic Case Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019399/
https://www.ncbi.nlm.nih.gov/pubmed/37363035
http://dx.doi.org/10.1007/s10668-023-03124-0
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