{"title":"2010-2019年全球有机农业研究绩效的科学计量图","authors":"Kaiyum Shaikh, Sibsankar Jana","doi":"10.1080/09737766.2021.2011629","DOIUrl":null,"url":null,"abstract":"This study covers the pattern of organic farming research performance at the global level. The scientific analysis and outcome citations are used to investigate the scientific representation of the country. This study is conducted based on the output publications in organic farming research during the period 2010 to 2019. A total number of 10704 publication data were collected from the Web of Science (WoS) core collection database. BibExcel, Vosviewer, R statistical software, and MS Excel are used for data analysis. The study found different aspects of organic farming research such as increment of publications, document types, prolific authors, network analysis of co-authorship, co-citations of authors, institutions, countries engaged, and source impact of publications. The maximum number of publications was in 2019 with 1413 records, and the minimum number of publications in 2010 with 796 records. The author Lal R has made the highest publications (66). This study indicates the annual scientific production of organic farming, the world perspectives of citation count, collaboration rate, and so on. Researchers have also indicated further research areas using databases such as Scopus, PubMed, and Chemical abstract.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"16 1","pages":"19 - 33"},"PeriodicalIF":1.6000,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Scientometric mapping of organic farming research performance in the global perspective during 2010-2019\",\"authors\":\"Kaiyum Shaikh, Sibsankar Jana\",\"doi\":\"10.1080/09737766.2021.2011629\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study covers the pattern of organic farming research performance at the global level. The scientific analysis and outcome citations are used to investigate the scientific representation of the country. This study is conducted based on the output publications in organic farming research during the period 2010 to 2019. A total number of 10704 publication data were collected from the Web of Science (WoS) core collection database. BibExcel, Vosviewer, R statistical software, and MS Excel are used for data analysis. The study found different aspects of organic farming research such as increment of publications, document types, prolific authors, network analysis of co-authorship, co-citations of authors, institutions, countries engaged, and source impact of publications. The maximum number of publications was in 2019 with 1413 records, and the minimum number of publications in 2010 with 796 records. The author Lal R has made the highest publications (66). This study indicates the annual scientific production of organic farming, the world perspectives of citation count, collaboration rate, and so on. Researchers have also indicated further research areas using databases such as Scopus, PubMed, and Chemical abstract.\",\"PeriodicalId\":10501,\"journal\":{\"name\":\"COLLNET Journal of Scientometrics and Information Management\",\"volume\":\"16 1\",\"pages\":\"19 - 33\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2022-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"COLLNET Journal of Scientometrics and Information Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09737766.2021.2011629\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"COLLNET Journal of Scientometrics and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09737766.2021.2011629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 2
摘要
本研究涵盖了全球有机农业研究绩效的模式。科学分析和结果引用用于调查国家的科学代表性。本研究基于2010年至2019年期间有机农业研究的产出出版物进行。从Web of Science(WoS)核心收集数据库中收集了10704份出版物数据。数据分析使用BibExcel、Vosviewer、R统计软件和MS Excel。该研究发现了有机农业研究的不同方面,如出版物的增加、文献类型、多产作者、合著者的网络分析、作者的共同引用、参与的机构、国家以及出版物的来源影响。出版物数量最多的是2019年的1413份记录,最小的是2010年的796份记录。作者Lal R的出版量最高(66)。这项研究表明了有机农业的年度科学产量、引用次数、合作率等世界视角。研究人员还使用Scopus、PubMed和Chemical abstract等数据库指出了进一步的研究领域。
Scientometric mapping of organic farming research performance in the global perspective during 2010-2019
This study covers the pattern of organic farming research performance at the global level. The scientific analysis and outcome citations are used to investigate the scientific representation of the country. This study is conducted based on the output publications in organic farming research during the period 2010 to 2019. A total number of 10704 publication data were collected from the Web of Science (WoS) core collection database. BibExcel, Vosviewer, R statistical software, and MS Excel are used for data analysis. The study found different aspects of organic farming research such as increment of publications, document types, prolific authors, network analysis of co-authorship, co-citations of authors, institutions, countries engaged, and source impact of publications. The maximum number of publications was in 2019 with 1413 records, and the minimum number of publications in 2010 with 796 records. The author Lal R has made the highest publications (66). This study indicates the annual scientific production of organic farming, the world perspectives of citation count, collaboration rate, and so on. Researchers have also indicated further research areas using databases such as Scopus, PubMed, and Chemical abstract.