A toolbox for brain network construction and classification (BrainNetClass) is a dataset published in Human Brain Mapping (2020). On theSindex it has a DataRank of 2.4, placing it in the top 9% of the data-sharing corpus. It has been cited 72 times, with 55 citing works in its 1-hop citation network. Its calibrated FAIR score is 54/100.
Ranks in the top 9% 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.
“https://github.com/zzstefan/BrainNetClass”
The dataset is identified by a web address (URL) rather than a persistent identifier scheme. [majority verdict 'partial' (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 code, toolbox manual, and testing data are available at https://github.com/zzstefan/BrainNetClass”
GitHub is named as the host, but it is not a curated data repository listed in re3data or FAIRsharing. [majority verdict 'partial' (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
“The code, toolbox manual, and testing data are available at https://github.com/zzstefan/BrainNetClass”
The dataset identifier appears only in the body text (data availability statement), not in the reference list. [majority verdict 'partial' (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 code, toolbox manual, and testing data are available at https://github.com/zzstefan/BrainNetClass”
The data availability statement points to a public repository (GitHub) containing the data, meeting Colavizza category 3. [majority verdict 'yes' (3/5 passes agreed)]
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 code, toolbox manual, and testing data are available at https://github.com/zzstefan/BrainNetClass.”— not found in the paper; verdict downgraded
The dataset's content is described in a running prose sentence listing three items, not in a dedicated structural section, table, or enumerated list. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (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 code, toolbox manual, and testing data are available at https://github.com/zzstefan/BrainNetClass”
The data availability statement provides a direct link to the data with no stated precondition. [majority verdict 'yes' (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
The paper does not label the access level of the data as 'open access', 'publicly available', or any other explicit term; it only states where the data can be accessed. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (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 released data (toolbox and testing datasets) are not sensitive human-subject data, and no gatekeeper is named.
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 paper does not state how long the data will be retained or preserved. [majority verdict 'no' (4/5 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 name any file format for the released data (code, manual, testing data). [majority verdict 'no' (2/5 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 community data or metadata standard (e.g., MIAME, BIDS, an ontology) is named as applied to the released data. [majority verdict 'no' (3/5 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'
“http://adni.loni.usc.edu”
The paper cites a URL for the ADNI database, which is an external resource identifier. [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'
No reuse license is stated for the data; the Creative Commons license applies only to the article.
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'
“BrainNetClass (v1.0) is available at https://github.com/zzstefan/BrainNetClass”
The paper gives a version token (v1.0) for the released code and data. [majority verdict 'yes' (3/5 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://github.com/zzstefan/BrainNetClass”
The code is available at a code-forge URL, which is a machine-resolvable locator. [majority verdict 'yes' (4/5 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)
“NIH grant (EB022880)”
The paper provides a specific grant number (EB022880) 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
The paper describes the toolbox's algorithms but does not name the specific instruments, software versions, or methods used to produce the released data (code and testing data). [majority verdict 'no' (3/5 passes agreed)]
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 toolbox, manual, and exemplary datasets are available”
A manual is named as a documentation object that accompanies the data. [majority verdict 'yes' (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
0.644
From this paper's citation signal
Citation Network Contribution
1.7
From 48 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 55 citers.
National Institutes of Health
Grant: AG041721
National Institutes of Health
Grant: AG042599
National Institutes of Health
Grant: EB022880
NIMH NIH HHS
Grant: P50 MH064065
NIA NIH HHS
Grant: R01 AG041721
NIA NIH HHS
Grant: R01 AG042599
NIBIB NIH HHS
Grant: R01 EB022880
National Institutes of Health
Grant: 5R01AG042599-03
Assessing Large-scale Brain Connectivities in Mild Cognitive Impairment
National Institutes of Health
Grant: 5R01AG041721-05
Quantifying Brain Abnormality by Multimodality Neuroimage Analysis
National Institutes of Health
Grant: 5R01EB022880-03
Diagnosis of Alzheimer's Disease Using Dynamic High-Order Brain Networks
FWCI
4.75
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Brain Network Construction and Classification Toolbox (BrainNetClass)