The use of quantitative, citation-based measures or indicators (e.g., citation counts, H-Index, Journal Impact Factor) in the evaluation of education and research in ways that are accurate, appropriate, transparent, and ethical.
Published in Chapter:
New Data-Related Roles for Librarians: Using Bibliometric Analysis and Visualization to Increase Visibility of Research Impact
Nandita S. Mani (University of North Carolina at Chapel Hill, USA), Barrie E. Hayes (University of North Carolina at Chapel Hill, USA), Adam Dodd (University of North Carolina at Chapel Hill, USA), Fei Yu (University of North Carolina at Chapel Hill, USA), and
Michelle A. Cawley (University of North Carolina at Chapel Hill, USA)
Copyright: © 2021
|Pages: 29
DOI: 10.4018/978-1-7998-7258-0.ch017
Abstract
From applying for competitive grants to showcasing institutional collaboration and research trends, the need for research institutions to demonstrate and increase visibility of research impact is growing. The authors discuss core competencies needed to support bibliometric research and present active and completed impact measurement and visualization (IMV) projects, providing examples from health sciences and academic collaborations. For those considering development of a similar area of expertise within their library, an overview of necessary skillsets, tools, and recommendations for team building and scalability are described. IMV has the potential to be developed in libraries and integrated across research domains. As library roles continue to shift to be more data-centric, it is ever more important for libraries to identify ways to expand information professionals' data skills so that they can be seen as indispensable partners in the data ecosystem.