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Knowledge Maps as Support Tool for Managing Scientific Competences: A Case Study at a Portuguese Research Institute

Author

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  • João Génio

    (IEETA/DETI, University of Aveiro, 3810-193 Aveiro, Portugal)

  • Alina Trifan

    (IEETA/DETI, University of Aveiro, 3810-193 Aveiro, Portugal)

  • António J. R. Neves

    (IEETA/DETI, University of Aveiro, 3810-193 Aveiro, Portugal)

Abstract

In a research organization, finding someone who is an expert in a field and that can take up a given role, defining areas of excellence, or employing a new member all require understanding the competences that are available in-house. This work explores the idea of using knowledge or competence maps as support tools for managing scientific competences. We implemented a use case at the Institute of Electronics and Informatics Engineering of Aveiro, a research institute at the University of Aveiro, but the methodology we proposed can be adapted to virtually any research organization. Knowledge maps are visual representations of information that can be designed with variable granularities with respect to the knowledge assets of an organization. From a research management perspective, knowledge maps support the discovery of research competences and provide an instant overview of a topic by showing the main areas at a glance. This solution explored in this work employed data mining approaches for gathering information from public databases and presenting it using knowledge maps. Other visualization tools, such as bar graphs, tables, filters and search functionalities, were created and integrated into a web platform. When put together, these components could turn the platform into a key component for the administration of a research organization.

Suggested Citation

  • João Génio & Alina Trifan & António J. R. Neves, 2023. "Knowledge Maps as Support Tool for Managing Scientific Competences: A Case Study at a Portuguese Research Institute," Publications, MDPI, vol. 11(1), pages 1-10, March.
  • Handle: RePEc:gam:jpubli:v:11:y:2023:i:1:p:19-:d:1103315
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    References listed on IDEAS

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    2. Xie, Zheng & Ouyang, Zhenzheng & Li, Jianping, 2016. "A geometric graph model for coauthorship networks," Journal of Informetrics, Elsevier, vol. 10(1), pages 299-311.
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