Koya, K. and Chowdhury, G. (2022) A quality and popularity based ranking method for research datasets. In: APIT 2022: 2022 4th Asia Pacific Information Technology Conference. APIT 2022: 4th Asia Pacific Information Technology Conference, 14-16 Jan 2022, Virtual conference. ACM Conference Proceedings . ACM Digital Library , pp. 103-110. ISBN 9781450395571
Abstract
Research outputs are the final products in the scientific research process and their quality is progressively being evaluated by various methods such as altmetrics, bibliometrics, impact factors and citation count etc. However, a significant component of scientific research involves creating/collecting/curating research datasets and globally, funding agencies and governments are mandating an open access policy on research datasets. Though repositories exist to store the datasets, there is no metricised guidance, indicating the quality of datasets for researchers wishing to reuse. We propose a novel method for ranking and visualising research datasets based on their quality and popularity, constructed through a normalised citation count since the year of origin, total cites and the impact factor of the journals which publish the articles citing the dataset. Additionally, we present the process flow for a proposed digital information system for the access of datasets according to their discipline and rank based on the variables. The proposed method is expected to assist researchers, globally, to choose the right datasets for their research, encourage researchers to share their datasets and promote interdisciplinary research.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 ACM. This is an author-produced version of a paper subsequently published in APIT 2022 Proceedings. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Research data; research data management; research data quality |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Jun 2022 14:03 |
Last Modified: | 21 Jun 2022 14:03 |
Status: | Published |
Publisher: | ACM Digital Library |
Series Name: | ACM Conference Proceedings |
Refereed: | Yes |
Identification Number: | 10.1145/3512353.3512368 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188266 |