Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

CSTs for Terabyte-Sized Data

PubMed(2022)10.1109/dcc52660.2022.00017Source: DataRank Database

CSTs for Terabyte-Sized Data is a research paper published in PubMed (2022). On theSindex it has a DataRank of 0. It has been cited 4 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access4 citations

Cite:

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?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (5 grants)OA: greenLinked Datasets (1)DataCite Reuse (1)IDs (PubMed, PMC)

Context only (not used in score)

Findable (2/2)

Accessible (1/2)

Interoperable (2/2)

Reusable (0/3)

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.

Live enrichment

National Science Foundation

Grant: 2013998

National Institutes of Health

Grant: HG011392,R01AI141810

NSERC

Grant: RGPIN-07185-2020

NIAID NIH HHS

Grant: R01 AI141810

NHGRI NIH HHS

Grant: R01 HG011392

greenLicense: https://doi.org/10.15223/policy-029

Recursive Parsing and Grammar Compression in the Era of Pangenomics (Invited Talk)

10.4230/lipics.wabi.2025.1Schloss Dagstuhl – Leibniz-Zentrum für Informatik