The Data Tags Suite (DATS) model for discovering data access and use requirements is a dataset published in GigaScience (2020). On theSindex it has a DataRank of 0.884, placing it in the top 22.8% of the data-sharing corpus. It has been cited 11 times, with 11 citing works in its 1-hop citation network.
Ranks in the top 23% for downstream scientific impact
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.373
From this paper's citation signal
Citation Network Contribution
0.511
From 8 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 11 citers.
National Institutes of Health
Grant: 1U24AI117966-01
National Institutes of Health
Grant: OTOD025462
National Science Foundation
Grant: OIA-1937136
National Science Foundation
Grant: R01GM118609
National Science Foundation
Grant: R01HL16835
NIAID NIH HHS
Grant: U24 AI117966
Biotechnology and Biological Sciences Research Council
Grant: BB/E025080/1
Biotechnology and Biological Sciences Research Council
Grant: BB/I000771/1
Biotechnology and Biological Sciences Research Council
Grant: BB/J020265/1
NICHD NIH HHS
Grant: P2C HD041028
MeSH Terms
Keywords
Peer review of "The Data Tags Suite (DATS) model for discovering data access and use requirements"
Peer review of "The Data Tags Suite (DATS) model for discovering data access and use requirements"
Peer review of "The Data Tags Suite (DATS) model for discovering data access and use requirements"