The hurdles of current data citation practices and the adding-value of providing PIDs below study level
Article No.: 41, Pages 1 - 5
Abstract
This paper discusses the data reuse principle from the end-user standpoint, addressing the data citation hurdles, particularly in the Social Sciences. Referencing research data and their inherited detailed entities by Persistent Identifiers (PIDs) supports FAIR data usage. However, in the Social Sciences, PIDs are only available on the study level, but not on the level of the inline data objects, such as survey variables. Since citing research data is the backbone of proper data reuse, this paper proposes an infrastructure to reference specific attributes within data sets, assigning PIDs to the finegrained level of attributes. By assigning PIDs to these attributes, individual elements of the data files can be referenced and retrieved with the required metadata for both machine-actionable as well as human access.
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- The hurdles of current data citation practices and the adding-value of providing PIDs below study level
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June 2022
392 pages
ISBN:9781450393454
DOI:10.1145/3529372
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Published: 20 June 2022
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JCDL '22: The ACM/IEEE Joint Conference on Digital Libraries in 2022
June 20 - 24, 2022
Cologne, Germany
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