🏆 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.

<i>Gaia</i> Data Release 2

Astronomy &amp; Astrophysics(2018)10.1051/0004-6361/201833051Source: DataRank Database

<i>Gaia</i> Data Release 2 is a dataset published in Astronomy &amp; Astrophysics (2018). On theSindex it has a DataRank of 9.9, placing it in the top 21.4% of the data-sharing corpus. It has been cited 8,630 times, with 154 citing works in its 1-hop citation network. Its calibrated FAIR score is 51/100.

Top 21%percentile
9.9DataRank
9.9Top 21%
Dataset Open Access8630 citations · base score 9.0
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Context. We present the second Gaia data release, Gaia DR2, consisting of astrometry, photometry, radial velocities, and information on astrophysical parameters and variability, for sources brighter than magnitude 21. In addition epoch astrometry and photometry are provided for a modest sample of minor planets in the solar system. Aims. A summary of the contents of Gaia DR2 is presented, accompanied by a discussion on the differences with respect to Gaia DR1 and an overview of the main limitations which are still present in the survey. Recommendations are made on the responsible use of Gaia DR2 results. Methods. The raw data collected with the Gaia instruments during the first 22 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into this second data release, which represents a major advance with respect to Gaia DR1 in terms of completeness, performance, and richness of the data products. Results. Gaia DR2 contains celestial positions and the apparent brightness in G for approximately 1.7 billion sources. For 1.3 billion of those sources, parallaxes and proper motions are in addition available. The sample of sources for which variability information is provided is expanded to 0.5 million stars. This data release contains four new elements: broad-band colour information in the form of the apparent brightness in the GBP (330–680 nm) and GRP (630–1050 nm) bands is available for 1.4 billion sources; median radial velocities for some 7 million sources are presented; for between 77 and 161 million sources estimates are provided of the stellar effective temperature, extinction, reddening, and radius and luminosity; and for a pre-selected list of 14 000 minor planets in the solar system epoch astrometry and photometry are presented. Finally, Gaia DR2 also represents a new materialisation of the celestial reference frame in the optical, the Gaia-CRF2, which is the first optical reference frame based solely on extragalactic sources. There are notable changes in the photometric system and the catalogue source list with respect to Gaia DR1, and we stress the need to consider the two data releases as independent. Conclusions. Gaia DR2 represents a major achievement for the Gaia mission, delivering on the long standing promise to provide parallaxes and proper motions for over 1 billion stars, and representing a first step in the availability of complementary radial velocity and source astrophysical information for a sample of stars in the Gaia survey which covers a very substantial fraction of the volume of our galaxy.

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.

    51FAIR score
    F Findable
    45
    A Accessible
    80
    I Interoperable
    38
    R Reusable
    42
    Top 21% 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 14%Citation Network 86%

    Base Score Contribution

    1.4

    From this paper's citation signal

    Citation Network Contribution

    8.5

    From 154 citing papers with measurable signal

    Learn more about DataRank methodology →

    Top 5 citers driving the network score

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

    1. The Two Micron All Sky Survey (2MASS)
      The Astronomical Journal200612,115 citationsDataRank 14.5Top 14%
    2. Extremely randomized trees
      Machine Learning20068,437 citationsDataRank 1.4
    3. The<i>Gaia</i>mission
      Astronomy &amp; Astrophysics20166,914 citationsDataRank 1.3
    4. IPython: A System for Interactive Scientific Computing
      Computing in Science &amp; Engineering20074,140 citationsDataRank 1.2
    Why this DataRank?

    DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 14% comes from its base citations and 86% from the citation network (154 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 (491)

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