Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients is a dataset published in Scientific Data (2022). On theSindex it has a DataRank of 0.965, placing it in the top 21% of the data-sharing corpus. It has been cited 57 times, with 34 citing works in its 1-hop citation network. Its calibrated FAIR score is 63/100.
Ranks in the top 21% for downstream scientific impact
Linked data & code
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.
“https://doi.org/10.6084/m9.figshare.c.5315474”
The dataset has a DOI as its persistent identifier, given in the reference list. [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'
“figshare”
The paper names figshare as the repository hosting the data. [majority verdict 'yes' (3/5 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
“93. Tian, Q. et al. Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients. figshare https://doi.org/10.6084/m9.figshare.c.5315474 (2021).”
The dataset appears as a reference-list entry (reference 93) with a DOI. [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 preprocessed diffusion MRI data and the T1-weighted MRI data of 26 healthy participants and the preprocessed rescan diffusion MRI data and the T1-weighted MRI data from seven of the 26 participants are publicly available through the figshare repository 93.”— not found in the paper; verdict downgraded
The Data Records section serves as the data availability statement and points to the figshare repository with a DOI (reference 93). [downgraded to 'partial' — 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
“Data Records”
The paper includes a formal 'Data Records' section that itemises the dataset contents (folder structure). [majority verdict 'yes' (3/5 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 preprocessed diffusion MRI data and the T1-weighted MRI data of 26 healthy participants and the preprocessed rescan diffusion MRI data and the T1-weighted MRI data from seven of the 26 participants are publicly available through the figshare repository 93.”— not found in the paper; verdict downgraded
The sentence states the data are publicly available with no precondition. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]
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”
The paper uses the phrase 'publicly available' to label the access level of the data. [majority verdict 'yes' (4/5 passes agreed)]
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 openly available with no gatekeeper named; the paper does not mention any institutional or personal gatekeeper.
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 preprocessed diffusion MRI data and the T1-weighted MRI data of 26 healthy participants and the preprocessed rescan diffusion MRI data and the T1-weighted MRI data from seven of the 26 participants are publicly available through the figshare repository 93.”— not found in the paper; verdict downgraded
The statement indicates availability now (timing) but does not mention how long the data will persist. [downgraded to 'no' — no verifiable quote from the paper] [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'
The paper does not specify any file format 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
The paper does not name a community data standard, checklist, or ontology; it only mentions software tools.
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'
“https://github.com/ksubramz/gradunwarp”
The paper gives a repository URL for third-party code used in data processing. [majority verdict 'yes' (3/5 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'
The paper only states the article license (CC BY 4.0), not a license for the dataset itself.
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'
The paper does not provide a version token or date to identify a specific snapshot of the data.
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://github.com/qiyuantian/GDSI”
The paper provides a URL to a GitHub repository containing the study's own code.
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)
“P41-EB015896”
The paper lists specific NIH grant numbers in the Acknowledgements.
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
“3 T Connectome MRI scanner (Magnetom CONNECTOM, Siemens Healthineers)”
The paper names the specific scanner and other instruments/software used to produce 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
“Folder 1: anat: T1-weighted MRI data corrected for gradient nonlinearity induced image distortion as well as a copy also corrected for spatially varying intensity bias.”— not found in the paper; verdict downgraded
The data description is inside the article, not a separate documentation object. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]
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
0.609
From this paper's citation signal
Citation Network Contribution
0.356
From 17 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 34 citers.
U.S. Department of Health & Human Services | NIH | National Institute on Aging
Grant: K99-AG073506
American Heart Association
Grant: 17POST33670452
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Grant: U01-EB026996
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Grant: R01-EB006847
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Grant: P41-EB015896
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Grant: P41-EB030006
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Grant: R00-EB015445
U.S. Department of Health & Human Services | NIH | National Institute of Mental Health
Grant: U01-MH093765
U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke
Grant: K23-NS078044
U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke
Grant: K23-NS096056
Massachusetts General Hospital
Grant: Claflin Distinguished Scholar Award
NCRR NIH HHS
Grant: S10 RR019307
NINDS NIH HHS
Grant: K23 NS096056
NIBIB NIH HHS
Grant: R01 EB006847
NIBIB NIH HHS
Grant: P41 EB030006
NIA NIH HHS
Grant: K99 AG073506
NIBIB NIH HHS
Grant: P41 EB015896
NCRR NIH HHS
Grant: S10 RR023043
NIMH NIH HHS
Grant: U01 MH093765
NCRR NIH HHS
Grant: S10 RR023401
NINDS NIH HHS
Grant: K23 NS078044
NIBIB NIH HHS
Grant: R00 EB015445
NINDS NIH HHS
Grant: R01 NS118187
NIBIB NIH HHS
Grant: U01 EB026996
National Institutes of Health
Grant: 1P41EB030006-01
Center for Mesoscale Mapping
National Institutes of Health
Grant: 5K23NS078044-03
Disconnection as a model for cognitive dysfunction in multiple sclerosis
National Institutes of Health
Grant: 5K23NS096056-02
Characterizing axonal damage in multiple sclerosis using TractCaliber MRI
National Institutes of Health
Grant: 1S10RR023401-01A2
A Storage Area Network for Structural and Functional Image Analysis
National Institutes of Health
Grant: 5U01MH093765-02
The Human Connectome Project (HCP)
National Institutes of Health
Grant: 1S10RR023043-01
SILICON GRAPHICS PRISM EXTREME 128P/1TB
National Institutes of Health
Grant: 5P41EB015896-18
Center for Functional Imaging Technologies
National Institutes of Health
Grant: 5R01EB006847-07
Parallel Excitation Methods for High Field MRI
National Institutes of Health
Grant: 5K99AG073506-02
Advancing methods for mapping short-range association fibers in the aging brain
National Institutes of Health
Grant: 4R00EB015445-03
Modeling TMS-induced Cortical Network Activity
National Institutes of Health
Grant: 1S10RR019307-01
Computeserver Structural &Functional Image Analysis
National Institutes of Health
Grant: 5U01EB026996-04
Connectome 2.0: Developing the next generation human MRI scanner for bridging studies of the micro-, meso- and macro-connectome
National Institutes of Health
Grant: 5R01NS118187-03
Toward a Validated in Vivo Imaging Marker of Axonal Damage Predictive of Progressive Disability in Multiple Sclerosis
U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke
National Multiple Sclerosis Society
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Fields of Study
MeSH Terms
Keywords
Metadata record for: Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
Metadata record for: Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients