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Browsing Waterloo Library by Subject "Bibliometrics"

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    Automating Big Data Cleaning: An Example Using Local Bibliometric Data
    (2017-04-06) Carson, Jana; Gordon, Shannon
    The University of Waterloo recognizes bibliometric data as an important piece of evidence-based research assessment, and recommends bibliometric data as one measure, among many, for capturing research productivity trends, and elements of research impact. Even when working from a basket of measures, bibliometric data remains complex and requires significant cleaning due to issues of name ambiguity. This session will explore an innovative collaboration between the Library and Institutional Analysis and Planning (IAP) to support the integrity of local, discipline-level bibliometric data by automating key data processes of an internal project. This session will introduce how bibliometric data is relevant to the University, the process used to gather and vet local bibliometric data, and the ways in which key data processes have been successfully automated using Python and a database to support efficient reporting. Given known challenges presented by name ambiguity, this collaborative framework makes it possible to support the integrity of local bibliometric data—a key step in supporting this and similar in-demand analyses at the University.
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    Bibliometrics and Research Impact at University of Waterloo: An Exciting Campus Partnership
    (University of Waterloo, 2017-04-03) Hitchens, Alison; Bèlanger, Annie
    In 2012, the Bibliometrics Working Group at the University of Waterloo, composed of the Library, the Office of Research, Institutional Analysis and Planning (IAP) and faculty representatives, began its work. In 2015, a new campus position was created, Bibliometrics and Research Impact Librarian, and the white paper “Measuring Research Outputs through Bibliometrics” was released. This specialist librarian also supports the Ranking Working Group and the Research Impact Working Group and is responsible for bibliometrics education across campus for our students and faculty. This Librarian has also been working to create a North American community of practice for bibliometrics work. This project briefing will highlight this campus partnership, lessons learned so far, and questions for future directions and infrastructure requirements for support. Additionally, we will explore possible connections between bibliometrics work, citation analysis and evidence-based collection development practices for a research-intensive University.
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    Collaborating to Automate Big Data Cleaning: An Example Using Local Bibliometric Data
    (2016-12-06) Carson, Jana; Gordon, Shannon
    This session will showcase a unique local collaboration between the Library, the Office of Research, and Institutional Analysis and Planning to support a project involving large amounts of complex data. The highly collaborative approach of this partnership made it possible to automate key data processes of an internal project which ultimately built valuable relationships between key campus units. In the academic environment, one common way to measure research productivity is by using counts of publications and their citations; often called bibliometric data. The University of Waterloo recognizes bibliometric data as an important piece of evidence-based research assessment, and recommends it as one measure, among many, for capturing research productivity trends, and elements of research impact. Centered on an example involving local bibliometric data, this session will introduce the relevance of this type of data to the University, and how leveraging the expertise and knowledge of others created a better final product, saved ~200 hours of manual work, and created a strong foundation for supporting similar projects. This collaborative framework has made it possible to support the integrity of local big data—a key step in supporting this and similar in-demand analyses at the University.
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    White Paper: Measuring Research Outputs Through Bibliometrics
    (University of Waterloo, 2016) University of Waterloo Working Group on Bibliometrics; Byl, Lauren; Carson, Jana; Feltracco, Annamaria; Gooch, Susie; Gordon, Shannon; Kenyon, Tim; Muirhead, Bruce; Seskar-Hencic, Daniela; MacDonald, Kathy; Özsu, M. Tamer; Stirling, Peter
    This White Paper provides a high-level review of issues relevant to understanding bibliometrics, and practical recommendations for how to appropriately use these measures. This is not a policy paper; instead, it defines and summarizes evidence that addresses appropriate use of bibliometric analysis at the University of Waterloo. Issues identified and recommendations will generally apply to other academic institutions. Understanding the types of bibliometric measures and their limitations makes it possible to identify both appropriate uses and crucial limitations of bibliometric analysis. Recommendations offered at the end of this paper provide a range of opportunities for how researchers and administrators at Waterloo and beyond can integrate bibliometric analysis into their practice.