Detecting glaucoma from multi-modal data using probabilistic deep learning is a dataset published in Frontiers in Medicine (2022). On theSindex it has a DataRank of 1.0, placing it in the top 19.8% of the data-sharing corpus. It has been cited 25 times, with 24 citing works in its 1-hop citation network. Its calibrated FAIR score is 10/100.
Ranks in the top 20% for downstream scientific impact
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Full FAIR picture · advisory
The headline score is computed from the scored criteria — the fact-shaped checks (a repository, an accession, a licence) that two independent models agree on. The advisory criteria below are real FAIR guidance but rest on judgment calls that models read differently, so they inform without moving the number.
No persistent identifier string (DOI, Handle, ARK, repository accession) is given for the study's own data.
RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit · RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier' · FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'
“The original contributions presented in this study are included in the article/Supplementary material”— not found in the paper; verdict downgraded
The data are said to be held in the article's supplementary material, which is a non-repository host (the journal's supplementary section). [downgraded to 'no' — no verifiable quote from the paper]
RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed ( · NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived · NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten
No identifier for the dataset appears anywhere in the text, either in the reference list or body.
FORCE11 Joint Declaration of Data Citation Principles (2014) — data should be cited as a first- · RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes · FsF-F3-01M — F-UJI: 'Metadata includes the identifier of the data it describes'
Advisory · not in the published score
“The original contributions presented in this study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author/s.”— not found in the paper; verdict downgraded
The statement points to the article and supplementary materials, which is Colavizza category 2 (data within the article). [downgraded to 'no' — no verifiable quote from the paper]
Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li · Springer Nature research data policy — Data Availability Statements: standard statement templat · RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes
“The development dataset included 840 fundus photographs, 840 visual fields, and 840 pairs of fundus photographs and visual fields from normal eyes and 815 fundus photographs, 815 visual fields, and 815 pairs of fundus photographs and visual fields from eyes with glaucoma.”
The dataset composition is described in a running prose sentence, not in an itemised section, table, or list.
RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential) · FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability' · FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'
“The original contributions presented in this study are included in the article/Supplementary material”— not found in the paper; verdict downgraded
The data are stated to be in the article and supplementary material, which are freely accessible without any precondition. [downgraded to 'partial' — no verifiable quote from the paper]
RDA-A1.1-01D — 'Data is accessible through a free access protocol' · FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data' · NSTC Desirable Characteristics of Data Repositories (2022) — 'Free and Easy Access'
Advisory · not in the published score
No explicit access-level label is applied to the data; the data availability statement only describes where the data are, not an access rights vocabulary term.
FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data' · RDA-A1-01M — metadata contains information to enable the user to get access to the data · COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl
“further inquiries can be directed to the corresponding author/s.”
The only gatekeeper named is a natural person (the corresponding author), not an institutional board or committee. [majority verdict 'partial' (3/5 passes agreed)]
NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee · RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and · NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse
“The original contributions presented in this study are included in the article/Supplementary material”— not found in the paper; verdict downgraded
The data are available immediately upon publication, but no retention period or permanent archival commitment is stated. [downgraded to 'no' — no verifiable quote from the paper]
NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines · NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy' · RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'
No file format token (e.g., JPEG, CSV) is specified for the released data.
FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co · RDA-R1.3-02D — data is expressed in a machine-understandable community standard · RDA-I1-01D — data uses a knowledge representation expressed in a standardised format
Advisory · not in the published score
No community data or metadata standard (e.g., MIAME, GO, FAIRsharing-registered) is named for the data.
RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential) · RDA-R1.3-01D — 'Data complies with a community standard' · RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'
No identifier for an external resource (e.g., other dataset, reference genome, code) is given in the text. [majority verdict 'no' (4/5 passes agreed)]
RDA-I3-01M — '(meta)data include references to other (meta)data' · RDA-I3-03M — 'metadata includes qualified references to other metadata' · FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'
No licence or reuse terms are explicitly attached to the data; the CC-BY licence covers the article, not the data. [majority verdict 'no' (3/5 passes agreed)]
RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu · RDA-R1.1-02M — 'Metadata refers to a standard reuse licence' · RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'
No version token or release date is given for the dataset; only the general collection period (2017) is mentioned.
DataCite Metadata Schema 4.6 — the 'Version' property · RDA-R1.2-01M — provenance information (which version was used is provenance) · NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'
Code availability is not addressed anywhere in the text.
NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code' · FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear · FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)
“This work was supported by NIH Grants EY033005 and EY031725 and a Challenge Grant from Research to Prevent Blindness (RPB), New York.”— not found in the paper; verdict downgraded
The paper provides specific award numbers (EY033005, EY031725) attached to a named funder (NIH), satisfying the grant-identifier requirement. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]
DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award · Crossref Funder Registry — canonical funder identifiers for funding metadata · RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco
Advisory · not in the published score
“Fundus photographs were collected using Compass (CMP, CenterVue, Padua, Italy) instruments.”— not found in the paper; verdict downgraded
The specific instrument (Compass) used to produce the data is named. [downgraded to 'partial' — no verifiable quote from the paper]
RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa · FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati · W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance
Neither a documentation object shipped with the data nor a variable-definition table inside the article is present.
RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu · FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data' · NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.489
From this paper's citation signal
Citation Network Contribution
0.534
From 19 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 24 citers.
National Eye Institute
Grant: EY033005
National Eye Institute
Grant: EY030142
National Eye Institute
Grant: EY031725
NEI NIH HHS
Grant: R01 EY033005
National Institutes of Health
Grant: 3R21EY031725-02S1
Improved Glaucoma Monitoring Using Artificial-Intelligence Enabled Dashboard
National Institutes of Health
Grant: 1R21EY030142-01
A hybrid artificial intelligence framework for glaucoma monitoring
National Institutes of Health
Grant: 5R01EY033005-04
Predicting the risk of glaucoma from structural, functional, and genetic factors using artificial intelligence
Research to Prevent Blindness
FWCI
2.60
Citation Percentile
0.9%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals