The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
The conundrum of sharing research data
Abstract
We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much‐improved data curation. (Hanson, Sugden, & Alberts, ) Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice.
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Cites
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Peng, R. D. (2011) · Science · doi:10.1126/science.1213847 · Cited by 1,449
Sharing Detailed Research Data Is Associated with Increased Citation Rate
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Two Bits: The Cultural Significance of Free Software
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Two Bits: The Cultural Significance of Free Software
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(2008) · doi:10.7551/mitpress/9780262151207.001.0001 · Cited by 286
Cited by
YFCC100M: the new data in multimedia research
Thomee, B., Shamma, D. A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., & Li, L.-J. (2016) · Communications of the ACM · doi:10.1145/2812802 · Cited by 1,541
MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain
Xia, Q., Sifah, E. B., Asamoah, K. O., Gao, J., Du, X., & Guizani, M. (2017) · IEEE Access · doi:10.1109/access.2017.2730843 · Cited by 1,148
Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., & Blackburn, J. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7347 · Cited by 881
Construction with digital twin information systems
Sacks, R., Brilakis, I., Pikas, E., Xie, H. S., & Girolami, M. (2020) · Data-Centric Engineering · doi:10.1017/dce.2020.16 · Cited by 609
“” Data-Centric Engineering e14-13 Kitchin (2014) reasoned that data refer to those elements that are “ taken ” (derived from the Latin “ capere ” ), for example, “ extracted through observations, computations, experiments, and record keeping ” (Borgman, 2012).”
BackgroundWallis, J. C., Rolando, E., & Borgman, C. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067332 · Cited by 495
Self-citation
Metadata
- Authors
- Borgman, C. L.
- Venue
- Journal of the American Society for Information Science and Technology
- Publisher
- Wiley
- Published
- 2012-04-05
- Volume
- 63
- Issue
- 6
- Pages
- 1059-1078
- ISSN
- 1532-2882 (ISSN-L)
- 1532-2890
- OpenAlex
- W3125261728
- Cited by
- 880
- References
- 7
- FWCI
- 157.26
- Type
- journal article
- Language
- en
- Open access
- closed
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