FAIR evaluation of public datasets for human stress detection

project

This project performs the FAIR evaluation of public datasets for human stress detection using the Fairshake dataset rubric. The five datasets are those identified by Mahesh et al. (https://ieeexplore.ieee.org/abstract/document/8730884)

Tags: stress datasets

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Project Assessments (6)


Assessment Metrics Date
Target Rubric   A standardized ID or accession number is used to identify the dataset. The dataset is described with metadata using a formal, broadly applicable vocabulary. Information is provided on the experimental methods used to generate the data. The dataset is hosted in an established data repository, if a relevant repository exists. The dataset can be downloaded for free from the repository. Version information is provided for the dataset. Contact information is provided for the creator(s) of the dataset. Information is provided describing how to cite the dataset. Licensing information is provided on the datasetÂ’s landing page.
DriveDB The FAIRshake dataset rubric
yes (1.00) no (0.00) yes (1.00) yes (1.00) yes (1.00) yes (1.00) yesbut (0.75) yes (1.00) yes (1.00) Apr 20, 2020
WESAD The FAIRshake dataset rubric
no (0.00) no (0.00) yes (1.00) yes (1.00) yes (1.00) nobut (0.25) yes (1.00) yes (1.00) nobut (0.25) Apr 20, 2020
DDD The FAIRshake dataset rubric
yes (1.00) no (0.00) yes (1.00) yes (1.00) yes (1.00) yes (1.00) nobut (0.25) yesbut (0.75) nobut (0.25) Apr 20, 2020
SUSAS The FAIRshake dataset rubric
no (0.00) no (0.00) yes (1.00) yes (1.00) no (0.00) no (0.00) nobut (0.25) nobut (0.25) yes (1.00) Apr 20, 2020
SWELL-KW The FAIRshake dataset rubric
yes (1.00) yes (1.00) yes (1.00) yes (1.00) yesbut (0.75) nobut (0.25) yes (1.00) yes (1.00) yes (1.00) May 20, 2020
WESAD The FAIRshake dataset rubric
                  Nov 5, 2024