Why data citation isn't working, and what to do about it. (12th May 2020)

• Record Type: Journal Article
• Authors: Buneman, Peter; Christie, Greig; Davies, Jamie A; Dimitrellou, Roza; Harding, Simon D; Pawson, Adam J; Sharman, Joanna L; Wu, Yinjun
• Is Part Of: Database. Volume 2020(2020)
• Publication Date: 2020-05-12
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/databa/baaa022
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: We describe a system that automatically generates from a curated database a collection of short conventional publications—citation summaries—that describe the contents of various components of the database. The purpose of these summaries is to ensure that the contributors to the database receive appropriate credit through the currently used measures such as h-indexes. Moreover, these summaries also serve to give credit to publications and people that are cited by the database. In doing this, we need to deal with granularity—how many summaries should be generated to represent effectively the contributions to a database? We also need to deal with evolution—for how long can a given summary serve as an appropriate reference when the database is evolving? We describe a journal specifically tailored to contain these citation summaries. We also briefly discuss the limitations that the current mechanisms for recording citations place on both the process and value of data citation.