🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge
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.

A catalog of numerical centrosome defects in epithelial ovarian cancers

EMBO Molecular Medicine(2022)10.15252/emmm.202215670Source: DataRank Database

A catalog of numerical centrosome defects in epithelial ovarian cancers is a dataset published in EMBO Molecular Medicine (2022). On theSindex it has a DataRank of 0.811, placing it in the top 44.3% of the data-sharing corpus. It has been cited 30 times, with 25 citing works in its 1-hop citation network. Its calibrated FAIR score is 25/100.

Top 44%percentile
0.811DataRank
0.811Top 44%
Dataset30 citations · base score 3.4
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 (0/2)
    Interoperable (0/2)
      Reusable (1/3)
      • Dataset classification

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

      25FAIR score
      F Findable
      40
      A Accessible
      35
      I Interoperable
      0
      R Reusable
      25
      Top 93% by FAIRLLM-assessed✓ full text read

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

      DataRank Breakdown

      Base Score 64%Citation Network 36%

      Base Score Contribution

      0.515

      From this paper's citation signal

      Citation Network Contribution

      0.296

      From 20 citing papers with measurable signal

      Learn more about DataRank methodology →

      Top 1 citer driving the network score

      Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

      Why this DataRank?

      DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 64% comes from its base citations and 36% from the citation network (20 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(Cq) ÷ max(outdegreeq, 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 →

      Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

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

      Authors (26)