Researcher perspectives on publication and peer review of data.
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In early 2014, we asked science and social science researchers... • What expectations do the terms publication and peer review raise in reference to data? • What features would be useful to evaluate the trustworthiness, evaluate the impact, and enhance the prestige of a data publication?
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Researcher perspectives on publication and peer review of data.
- 1. Researcher perspectives on publication and peer review of data Government Academic (teaching) Academic (medical) Nonprofit Commercial United States: 80% UK 4% CA 4% Country Other Principal Investigator 41% Postdoc 24% Grad student 16% Tech 11% Other 7% Role Biology 37% Archaeology 13% Social sci. 13% Env. sci. 11% Discipline 7% 5% 4% 1 Other 9% Physical sci. Earth sci. Comp. sci. Math Academic (research): 76% 6% 5% 5% 4% 2 2 Institution N= 249 If you published on someone else’s dataset, how did you credit the dataset creator(s)? If someone published on your dataset, how did you feel about the credit you recieved? ∅ informal citation authorship acknowledgment formal citation How should a dataset creator be credited? 75 39 63 14 63 23 50 n = 249 n = 129 insufficient appropriate excessive 0 100% n = 86 63 17 5 13 2 0 50% 100% informal citation authorship acknowledgment formal citation How would you expect a published dataset to differ from a shared one? Rich metadata Basis of a research paper Deposited in a repository Openly available Described in a data paper Peer-reviewed Formal metadata Has a unique identifier What would you expect data peer review to consider? Methods are appropriate Enough metadata for replication Metadata properly standardized Technical details check out Data is plausibile Novel/impactful 68 54 43 39 39 28 25 22 80 70 61 39 22 n = 246 n = 244 Deposited in a repository Formal metadata Openly available Rich metadata Unique identifier Peer-reviewed Basis of a research paper Described in a data paper Enough metadata to replicate Methods are appropriate Metadata properly standardized Technical details check out Data is plausibile Novel/ impactful Low Citations Downloads Search rank Altmetrics Traditional paper Peer-reviewed data paper Peer-reviewed dataset Un-peer-reviewed data paper Un-peer-reviewed dataset How much weight would you give each item on a researcher’s CV? How useful is each metric in assessing dataset value/impact? Basis of a traditional paper Described by a data paper Successfullly reused Peer-reviewed How much confidence in a dataset does each attribute inspire? 0 50% 100% Moderate High 0 50% 100% 242 ≤ n ≤ 247 242 ≤ n ≤ 244 238≤ n ≤ 241 90 • What expectations do the terms publication and peer review raise in reference to data? • What features would be useful to evaluate the trustworthiness, evaluate the impact, and enhance the prestige of a data publication? • Two predominant notions of publication center around (1) access and (2) the traditional literature • Peer review is not expected, but it is valuable to establish trust and prestige. • Citation counts are the most useful measure of impact, but download counts are also valuable. • Researchers agree that data should be cited formally in the reference list. • 68% had shared data; 58% of those had seen the data reused; 61% of the reuses led to a publication. • 61% had reused someone’s data; 69% of the reuses led to a publication. Demographics John Ernest Kratz 0000-0002-9610-5370 John.Kratz@ucop.edu @john_kratz Carly Strasser 0000-0001-9592-2339 Carly.Strasser@ucop.edu @carlystrasser In early 2014, we asked science and social science researchers... Conclusions