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Experts’ Evaluation: Datasets of Rating Questionnaires for the HEUROBOX Heuristics to Evaluate Industrial Collaborative Robotic Environments

dc.rights.licenseAttribution 4.0 International*
dc.contributor.authorApraiz, Ainhoa
dc.contributor.authorMulet Alberola, Jose Antonio
dc.contributor.authorLasa, Ganix
dc.contributor.authorMazmela Etxabe, Maitane
dc.contributor.authorNguyen Thi Ngoc, Hien
dc.date.accessioned2026-06-05T13:48:02Z
dc.date.available2026-06-05T13:48:02Z
dc.date.issued2023
dc.identifierhttps://data.mendeley.com/datasets/t2nwpwwsmg/1en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/14500
dc.descriptionThis study presents a dataset derived from expert evaluation aimed at assessing two aspects: (1) the usability of a newly developed set of heuristics (HEUROBOX), and (2) the relative importance of heuristic categories in evaluating collaborative robotic environments for industrial applications. The experts were carefully selected based on their expertise in various relevant fields, including collaborative robotics, human factors, biomechanics, and manufacturing. Their evaluations were obtained through the System Usability Scale (SUS) questionnaire and category-rating questionnaires, which were employed in conjunction with the Analytical Hierarchy Process (AHP) methodology. The resulting dataset was analyzed using AHP algorithms implemented in the R programming language. The transparency of both the data and the code allows design practitioners and researchers to utilize them for replication and further analysis, thereby adhering to the principles of reproducible research in the context of multiple-criteria decision analysis.en
dc.language.isoengen
dc.rights© The Author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectApplied Mathematicsen
dc.subjectDecision Scienceen
dc.subjectPsychometricsen
dc.titleExperts’ Evaluation: Datasets of Rating Questionnaires for the HEUROBOX Heuristics to Evaluate Industrial Collaborative Robotic Environmentsen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
local.contributor.groupInnovación en Diseño Industriales
local.identifier.doihttps://doi.org/10.17632/t2nwpwwsmg.1en
oaire.format.mimetypeapplication/zipen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_ddb1en
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85en
dc.unesco.tesaurohttp://vocabularies.unesco.org/thesaurus/concept6459en
oaire.funderNameComisión Europeaen
oaire.funderNameGobierno Vascoen
oaire.funderIdentifierhttps://ror.org/00k4n6c32 / http://data.crossref.org/fundingdata/funder/10.13039/501100000780en
oaire.funderIdentifierhttps://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086en
oaire.fundingStreamH2020en
oaire.fundingStreamElkartek 2019en
oaire.awardNumber737422en
oaire.awardNumberKK-2019-00035en
oaire.awardTitleSecure Connected Trustable Things (SCOTT)en
oaire.awardTitlePreparación tecnológica para la automatización multivehicular para el sector industrial (AUTOLIB)en
oaire.awardURIhttps://doi.org/10.3030/737422en
dc.unesco.clasificacionhttp://skos.um.es/unesco6/331003en


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