TY - GEN
T1 - A FAIR evaluation of public datasets for stress detection systems
AU - Cuno, Alvaro
AU - Condori-Fernandez, Nelly
AU - Mendoza, Alexis
AU - Lovon, Wilber Ramos
PY - 2020/12/9
Y1 - 2020/12/9
N2 - Nowadays, datasets are an essential asset used to train, validate, and test stress detection systems based on machine learning. In this paper, we used two sets of FAIR metrics for evaluating five public datasets for stress detection. Results indicate that all these datasets comply to some extent with the (F)indable, (A)ccessible, and (R)eusable principles, but none with the (I)nteroperable principle these findings contribute to raising awareness on (i) the need for the FAIRness development and improvement of stress datasets, and (ii) the importance of promoting open science in the affective computing community.
AB - Nowadays, datasets are an essential asset used to train, validate, and test stress detection systems based on machine learning. In this paper, we used two sets of FAIR metrics for evaluating five public datasets for stress detection. Results indicate that all these datasets comply to some extent with the (F)indable, (A)ccessible, and (R)eusable principles, but none with the (I)nteroperable principle these findings contribute to raising awareness on (i) the need for the FAIRness development and improvement of stress datasets, and (ii) the importance of promoting open science in the affective computing community.
KW - Datasets
KW - FAIR principles
KW - Stress detection
UR - http://www.scopus.com/inward/record.url?scp=85098624680&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098624680&partnerID=8YFLogxK
U2 - 10.1109/SCCC51225.2020.9281274
DO - 10.1109/SCCC51225.2020.9281274
M3 - Conference contribution
AN - SCOPUS:85098624680
T3 - Proceedings - International Conference of the Chilean Computer Science Society, SCCC
BT - 2020 39th International Conference of the Chilean Computer Science Society, SCCC 2020
PB - IEEE Computer Society
T2 - 39th International Conference of the Chilean Computer Science Society, SCCC 2020
Y2 - 16 November 2020 through 20 November 2020
ER -