Metadata implementation and data discoverability: A survey on university libraries' Dataverse portals
The purpose of this practical case study is to examine the development of Dataverse, a global research data management consortium. This paper is the second in a project focusing on data discoverability and current metadata implementation on the Dataverse portals established by 27 university libraries worldwide. Five research questions were proposed to identify the most popular metadata standards and elements, search interface options, and result display formats by those portals. The data were collected from 27 university libraries worldwide between December 1, 2020 and January 31, 2021. According to the results of the descriptive analyses, the most popular metadata elements for the dataset overview were Subject and Description, while Dataset persistent ID, Publication Date, Title, Author, Contact, Deposit Date, Depositor, Description, and Subject were the most popular elements for the metadata record of each dataset. Publication Year, Author Names, and Subject were found to be the most common search facets used by the portals. English was the most common language used for the search interfaces and metadata descriptions. Based on their findings from this evidence-based study, the authors recommend future research on the development of institutional data portal infrastructure, on stakeholder outreach and training, and on user studies on dataset retrieval.
The Journal of Academic Librarianship
Chiu, Tzu-Heng; Chen, Hsin-liang (Oliver); and Cline, Ellen, "Metadata implementation and data discoverability: A survey on university libraries' Dataverse portals" (2023). PCOM Scholarly Papers. 2206.
Available for download on Friday, May 10, 2024
This article was published in The Journal of Academic Librarianship, Volume 49, Issue 4.
The published version is available at https://doi.org/10.1016/j.acalib.2023.102722.
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