A continuous pursuit dataset for online deep learning-based EEG brain-computer interface is a dataset published in Scientific Data (2024). On theSindex it has a DataRank of 0.249, placing it in the top 59.9% of the data-sharing corpus. It has been cited 4 times, with 4 citing works in its 1-hop citation network. Its calibrated FAIR score is 71/100.
Ranks in the top 60% 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://doi.org/10.1184/R1/25360300”
The paper provides a DOI for its own dataset.
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'
“This dataset was uploaded to the Figshare (https://figshare.com) platform”
Figshare is a named data repository. [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
“Forenzo, D. & He, B. EEG-BCI Dataset for 'Continuous Tracking using Deep Learning-based Decoding for Non-invasive Brain-Computer Interface'. figshare https://doi.org/10.1184/R1/25360300 (2024).”— not found in the paper; verdict downgraded
The dataset appears as a reference-list entry. [downgraded to 'partial' — no verifiable quote from the paper] [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
“This dataset was uploaded to the Figshare (https://figshare.com) platform and can be accessed at: https://doi.org/10.1184/R1/25360300)47.”
The Data access statement points to a repository record with a DOI, fulfilling 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
“A full list of all the sub-fields included in the MATLAB structs is shown in Table 3, along with the data type and a brief description of each of the fields.”
An itemized inventory of the dataset fields is given in a table.
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'
“This dataset was uploaded to the Figshare (https://figshare.com) platform and can be accessed at: https://doi.org/10.1184/R1/25360300)47.”
The paper gives a direct link to the dataset on Figshare with no stated precondition for access, indicating unconditional availability. [majority verdict 'yes' (3/5 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
“By providing this dataset to the public, we hope to help facilitate the development of new or improved BCI decoding algorithms”
The paper states the dataset is provided to the public but does not use an explicit access-level label such as 'open access' or 'publicly available' for the data itself; the access action is described but not labeled. [majority verdict 'partial' (3/5 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
“informed consent for the experimental procedure, including data sharing, was obtained from each subject via written consent form.”
The data are human-subject but shared openly with consent; no institutional 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
No sentence states when the data become available beyond the present or how long they persist.
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'
“MATLAB files (' .mat')”
The data are in .mat format, which is proprietary (MATLAB).
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 or metadata community standard (ontology, checklist, schema) is named.
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'
“Code relevant to the analysis of this dataset is available at: https://github.com/bfinl/CPDL.”
The paper gives a URL identifier for the code that it wrote. [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 text.
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 pin the data snapshot.
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 relevant to the analysis of this dataset is available at: https://github.com/bfinl/CPDL.”
A machine-resolvable code repository URL is given.
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 in part by NIH grants AT009263, NS127849, NS096761, NS131069, NS124564, and EB029354.”
The paper provides award numbers from a named funder.
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
“64-channel Neuroscan Quik-caps with the SynAmps/RT amplifiers”
The paper names the specific instruments used to produce the data. [majority verdict 'yes' (4/5 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
“A similar list is also provided in the README file included with the dataset in the Figshare repository, which also provides more detailed descriptions of each of the struct fields.”
A README file is named as accompanying the data.
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
0.241
From this paper's citation signal
Citation Network Contribution
7.29 × 10⁻³
From 1 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 4 citers.
U.S. Department of Health & Human Services | NIH | National Center for Complementary and Integrative Health
Grant: AT009263
U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke
Grant: NS127849, NS096761, NS131069, NS124564
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
Grant: EB029354
National Institutes of Health
Grant: 2R01NS096761-06
Electrophysiological Source Imaging of Partial Epilepsy
National Institutes of Health
Grant: 1R01NS127849-01A1
Imaging Epilepsy Sources with Biophysically Constrained Deep Neural Networks
National Institutes of Health
Grant: 1U18EB029354-01
Treating pain in sickle cell disease by means of focused ultrasound neuromodulation
National Institutes of Health
Grant: 1R01NS124564-01
Characterization of in vivo neuronal and inter-neuronal responses to transcranial focused ultrasound
National Institutes of Health
Grant: 1RF1NS131069-01
Electrophysiology-Compatible Wearable Transcranial Focused Ultrasound Neuromodulation Array Probes
National Institutes of Health
Grant: 5R01AT009263-06
Mind-body awareness training and brain-computer interface
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals