🏆 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.

SHARE: A Semantic Web Query Engine for Bioinformatics

Lecture Notes in Computer Science(2009)10.1007/978-3-642-10871-6_27Source: DataRank Database

SHARE: A Semantic Web Query Engine for Bioinformatics is a research paper published in Lecture Notes in Computer Science (2009). On theSindex it has a DataRank of 0.483. It has been cited 24 times.

N/A
0.483DataRank · unranked
0.483
24 citations · base score 3.2
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 (0/3)

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

        DataRank Breakdown

        Base Score 100%Citation Network 0%

        Base Score Contribution

        0.483

        From this paper's citation signal

        Citation Network Contribution

        0

        Citation network not refreshed for this result

        This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

        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 100% comes from its base citations and 0% from the citation network.

        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 →

        Authors (3)

        Mark D D. WilkinsonORCID,Erin McCarthyORCID,Ben P. Vandervalk

        Related Papers (10)

        2009 IEEE Asia-Pacific Services Computing Conference (APSCC)(2009)
        co-cited
        10.1109/apscc.2009.5394148
        Lecture Notes in Computer Science(2004)
        co-citedsame journal
        10.1007/978-3-540-30475-3_25
        Briefings in Bioinformatics(2002)
        co-cited
        10.1093/bib/3.4.331
        Tools in Scientific Workflow Composition
        N/A
        0.165DataRank · unranked
        Lecture Notes in Computer Science(2010)
        co-citedsame journal
        10.1007/978-3-642-16558-0_22
        Lecture Notes in Computer Science(2010)
        co-citedsame journal
        10.1007/978-3-642-16558-0_26
        Briefings in Bioinformatics(2008)
        co-cited
        10.1093/bib/bbn003