A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation is a dataset published in Scientific Data (2024). On theSindex it has a DataRank of 0.692, placing it in the top 28.9% of the data-sharing corpus. It has been cited 19 times, with 18 citing works in its 1-hop citation network. Its calibrated FAIR score is 79/100.
Ranks in the top 29% 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.
“Calabrese, E. & LaBella, D. BraTS Meningioma Dataset. Synapse https://doi.org/10.7303/syn51514106 (2023).”
The dataset identifier is a DOI (10.7303/syn51514106) which is a persistent identifier scheme. [majority verdict 'yes' (4/5 passes agreed)]
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 BraTS Meningioma Pre-operative Dataset training (1,000/1,424, 70%) and validation (141/1,424, 10%) data are publicly available on Synapse 14.”
Synapse is named as the repository holding the data. [majority verdict 'yes' (4/5 passes agreed)]
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
“Calabrese, E. & LaBella, D. BraTS Meningioma Dataset. Synapse https://doi.org/10.7303/syn51514106 (2023).”
The dataset appears as a reference-list entry in the References section. [majority verdict 'yes' (4/5 passes agreed)]
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 BraTS Meningioma Pre-operative Dataset training (1,000/1,424, 70%) and validation (141/1,424, 10%) data are publicly available on Synapse 14.”
The Data Records section points to a repository record with a DOI.
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 BraTS Meningioma Pre-operative Dataset training (1,000/1,424, 70%) and validation (141/1,424, 10%) data are publicly available on Synapse 14.”
The dataset description is given in running prose rather than an itemised inventory of files, variables, or records. [majority verdict 'partial' (2/5 passes agreed)]
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 BraTS Meningioma Pre-operative Dataset training (1,000/1,424, 70%) and validation (141/1,424, 10%) data are publicly available on Synapse 14.”
The text states the data are publicly available with no precondition.
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
“publicly available on Synapse 14”
The paper uses the phrase 'publicly available' which is a natural-language equivalent of the open access label.
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
The data are publicly available and no gatekeeper is named; the paper states the data are openly accessible on Synapse.
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
No sentence states how long the data will persist or when they become available beyond the current release. [majority verdict 'no' (3/5 passes agreed)]
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'
“conversion from Digital Imaging and Communications in Medicine (DICOM) format to Neuroimaging Informatics Technology Initiative (NIfTI) format”
NIfTI is an open, community-standard file format. [majority verdict 'yes' (3/5 passes agreed)]
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 data/metadata community standard such as MIAME, BIDS, or an ontology is named; the paper mentions clinical and imaging standards (CNS WHO, DICOM) but not as a community standard for the data. [majority verdict 'no' (4/5 passes agreed)]
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'
“The nnU-Net model as used for initial pre-automated segmentation is publicly available at (https://github.com/ecalabr/nnUNet_models).”
A URL identifier is given for the code repository used in the study. [majority verdict 'yes' (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 license for the data is stated in the paper; the article's CC-BY license applies to the article, not the data.
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 date is given to identify a specific snapshot of the data. [majority verdict 'no' (4/5 passes agreed)]
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'
“https://fets-ai.github.io/Front-End/”
The paper provides a machine-resolvable URL for the FeTS toolkit used in the study, fulfilling the code availability criterion. [majority verdict 'yes' (3/5 passes agreed)]
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)
“U24CA279629, U01CA242871, NCI K08CA256045, and NCI/ITCR U01CA242871”
Award/grant numbers are given for the funding.
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
“nnU-Net (version 1) (https://github.com/MIC-DKFZ/nnUNet/tree/nnunetv1)”
A specific software tool and version is named for producing the data.
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
“The 'Meningioma supplementary clinical data and imaging parameters for training and validation sets.xlsx' file on the Synapse data repository describes the case level clinical patient data and the image parameters for the training and validation cases 14.”— not found in the paper; verdict downgraded
A documentation file (Excel spreadsheet) is named as accompanying the data on the repository. [downgraded to 'partial' — no verifiable quote from the paper]
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
0.449
From this paper's citation signal
Citation Network Contribution
0.243
From 7 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 18 citers.
Foundation for the National Institutes of Health
Grant: NCI/ITCR U01CA242871
Foundation for the National Institutes of Health
Grant: NCI K08CA256045
Foundation for the National Institutes of Health
Grant: U01CA242871
Foundation for the National Institutes of Health
Grant: U24CA279629
NCI NIH HHS
Grant: K08 CA256045
National Institutes of Health
Grant: 5U01CA242871-02
The Federated Tumor Segmentation (FeTS) platform: An intuitive tool facilitating secure multi-institutional collaboration
National Institutes of Health
Grant: 5U24CA279629-02
Privacy-Aware Federated Learning for Breast Cancer Risk Assessment
National Institutes of Health
Grant: 5K08CA256045-03
Enhancing the efficacy of Radiation Therapy for brainstem glioma by targeting ATM
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals