Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

August 2021 data-update for "Updated science-wide author databases of standardized citation indicators"

(2021)10.17632/btchxktzyw.3Source: DataRank Database

August 2021 data-update for "Updated science-wide author databases of standardized citation indicators" is a dataset (2021). On theSindex it has a DataRank of 0.574, placing it in the top 47.3% of the data-sharing corpus. It has been cited 9 times, with 9 citing works in its 1-hop citation network. Its calibrated FAIR score is 29/100.

Top 47%percentile

0.574DataRank

0.574Top 47%

Dataset Open Access9 citations · base score 2.3

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

›Data sources & pipeline

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Pending

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (1/3)

Dataset classification

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

29FAIR score

F Findable

A Accessible

I Interoperable

R Reusable

Top 90% by FAIRLLM-assessed

Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →

DataRank Breakdown

Base Score 60%Citation Network 40%

Base Score Contribution

0.345

From this paper's citation signal

Citation Network Contribution

0.229

From 5 citing papers with measurable signal

Learn more about DataRank methodology →

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 60% comes from its base citations and 40% from the citation network (5 citing papers contributed measurable signal).

Base score B(p): log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
Network N(p): Σ over citers of log1p(C_q) ÷ max(outdegree_q, 1). Being cited by a highly-cited paper with few references counts most.
Damping factor d = 0.85: DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
Self-citations excluded: Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

Read the full methodology →

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Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank