Time event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events is a dataset published in Journal of the American Medical Informatics Association (2020). On theSindex it has a DataRank of 1.5, placing it in the top 13.8% of the data-sharing corpus. It has been cited 34 times, with 32 citing works in its 1-hop citation network.
Ranks in the top 14% for downstream scientific impact
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
0.533
From this paper's citation signal
Citation Network Contribution
0.966
From 20 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 32 citers.
National Institutes of Health
Grant: R01LM011829
National Institutes of Health
Grant: R01AI130460
Cancer Prevention and Research Institute of Texas
Grant: # RP160015
National Institutes of Health
Grant: 1R01AI130460-01
Dynamic learning for post-vaccine event prediction using temporal information in VAERS
National Institutes of Health
Grant: 5R01LM011829-03
Patient Medical History Representation, Extraction, and Inference from EHR Data
UTHealth Innovation for Cancer Prevention Research Training Program Pre-Doctoral Fellowship
FWCI
2.20
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals