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Abstract

Research data are a variety of products produced during research that are collected, observed, or created for purposes of analysis to produce original research results. This may come in the form of instrument measurements, experimental observations, still images, video and audio, text documents, spreadsheets, databases, quantitative data (e.g., household survey data), survey results and interview transcripts, simulation data, models and software, slides, artifacts, specimens, samples, sketches, diaries, lab notebooks, and the list goes on.

Depending on the infrastructure available to them, librarians can integrate data catalogs with library retrieval services such as Koha, Alma, WorldShare Management Services (WMS), and Sierra among others, making data search easier. Data management librarians provide advice on conditions under which datasets can be reused and promote the use of common standards and tools among researchers. This is how it is possible for researchers to relate to the research data lifecycle, data analysis, tools, and statistics (Chiware, 2015).

Because librarians curate and preserve datasets, they can help researchers understand their metadescriptions. It is therefore important for them to guide researchers on discipline-specific best practices in data creation and intellectual property rights, research data management support, including data management plans for grant applications, intellectual property rights advice, and the integration of data management into the curriculum. Librarians also guide and support data creators on bibliometrics (for example, by explaining impact factor, h-index) and altmetrics facilitated with the use of tools such as Mendeley, Scopus author management, ORCID identifier, and Data Management Plan Tool (Chiware, 2015).

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/content/papers/10.5339/qproc.2022.ehil2021.2
2022-01-13
2022-10-05
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References

  1. Chiware, E., & Mathe, Z.. (2015). Academic libraries’ role in research data management services: a South African perspective. South African Journal of Libraries and Information Science, 81:(2), 1-10. https://doi.org/10.7553/81-2-1563
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.5339/qproc.2022.ehil2021.2
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