Naimat Ullah Shah, Nusrat Ali, Aamir Hamid, Muhammad Ajmal Khan
{"title":"Research visualization trends in research data management (RDM): a bibliometric analysis","authors":"Naimat Ullah Shah, Nusrat Ali, Aamir Hamid, Muhammad Ajmal Khan","doi":"10.1108/gkmc-09-2023-0349","DOIUrl":null,"url":null,"abstract":"Purpose\nThis study aims to examine research visualization trends in research data management (RDM), analyzing factors such as contributions, publications, document types, authors and research areas, emphasizing the dynamic nature of RDM research in the scholarly landscape.\n\nDesign/methodology/approach\nThe study analyzed citation histories for 1,401 publications from 2001 to 2021 in the Web of Science database, extracting no restrictions on document type or language. Literature visualization tools such as Biblioshiny, VOSviewer, ScientoPy and MS Excel were used. The researchers explored institutional collaborations, data-centric trends and RDM frontiers.\n\nFindings\nThe majority of RDM research is conducted by librarians and information scientists. Research on RDM has increased over the past 21 years, peaking in 2019. Among universities, Sheffield and Pittsburgh have the most productivity in RDM research, and the USA is the most productive country. Most productive authors are Aleixandre-Benavent-R and Da Silva Jr. RDM; however, improvement is still needed, especially at academic universities.\n\nOriginality/value\nThis study provides valuable insights into the published literature on RDM and identifies patterns of collaboration among researchers in RDM.\n","PeriodicalId":507843,"journal":{"name":"Global Knowledge, Memory and Communication","volume":"32 26","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Knowledge, Memory and Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/gkmc-09-2023-0349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
This study aims to examine research visualization trends in research data management (RDM), analyzing factors such as contributions, publications, document types, authors and research areas, emphasizing the dynamic nature of RDM research in the scholarly landscape.
Design/methodology/approach
The study analyzed citation histories for 1,401 publications from 2001 to 2021 in the Web of Science database, extracting no restrictions on document type or language. Literature visualization tools such as Biblioshiny, VOSviewer, ScientoPy and MS Excel were used. The researchers explored institutional collaborations, data-centric trends and RDM frontiers.
Findings
The majority of RDM research is conducted by librarians and information scientists. Research on RDM has increased over the past 21 years, peaking in 2019. Among universities, Sheffield and Pittsburgh have the most productivity in RDM research, and the USA is the most productive country. Most productive authors are Aleixandre-Benavent-R and Da Silva Jr. RDM; however, improvement is still needed, especially at academic universities.
Originality/value
This study provides valuable insights into the published literature on RDM and identifies patterns of collaboration among researchers in RDM.