Scientific Collaboration Network Views: A Brazilian Computer Science Graduate Programs Case

Authors

  • Aurelio Ribeiro Costa University of Brasília
  • Vanessa Tavares Nunes University of Brasília
  • Célia Ghedini Ralha University of Brasília

DOI:

https://doi.org/10.5753/jidm.2022.2695

Keywords:

design science research, digital libraries, scientific interactions, social networks

Abstract

Scientific collaboration networks can present different views of researchers’ interactions. This work presents SCI-synergy, an online navigable artifact aiming to promote mechanisms and views of scientific collaboration networks. The artifact focuses on the researchers’ interaction in the co-authorship of publications considering intra- and interprogram relationships. SCI-synergy is developed upon the design science research paradigm using scientific publication data available on the large Digital Bibliography & Library Project (DBLP) repository. Official data from the Sucupira repository of six Brazilian graduate program members including Federal University of Minas Gerais (UFMG), State University of São Paulo (USP), Federal University of Rio Grande do Norte (UFRN), Federal University of Amazonas (UFAM), University of Brasília (UnB), and University of Vale do Rio dos Sinos (UNISINOS) is used. Data from these graduate programs illustrate the artifact usage regarding the scientific collaboration network of each program, how each researcher cooperates, and what relationship patterns exist in intra- and inter-programs views. We advocate that, even though it is necessary to consider data from each program’s history and current contextualization regarding politics, economics, and administration, the collaboration network views provided by SCI-synergy might help to understand collaboration network patterns.

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Published

2022-10-03

How to Cite

Ribeiro Costa, A., Tavares Nunes, V., & Ghedini Ralha, C. (2022). Scientific Collaboration Network Views: A Brazilian Computer Science Graduate Programs Case. Journal of Information and Data Management, 13(4). https://doi.org/10.5753/jidm.2022.2695

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Section

Regular Papers