Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/46380

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dc.contributor.authorCosta, Carlospor
dc.contributor.authorSantos, Maribel Yasminapor
dc.date.accessioned2017-09-07T17:26:13Z-
dc.date.issued2017-
dc.identifier.citationCosta, Carlos and Maribel Yasmina Santos, “The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age”, International Journal of Information Management, http://dx.doi.org/10.1016/j.ijinfomgt.2017.07.010por
dc.identifier.issn0268-4012-
dc.identifier.urihttps://hdl.handle.net/1822/46380-
dc.description.abstractThe activities in our current world are mainly supported by data-driven web applications, making extensive use of databases and data services. Such phenomenon led to the rise of Data Scientists as professionals of major relevance, which extract value from data and create state-of-the-art data artifacts that generate even more in- creased value. During the last years, the term Data Scientist attracted significant attention. Consequently, it is relevant to understand its origin, knowledge base and skills set, in order to adequately describe its profile and distinguish it from others like Business Analyst. This work proposes a conceptual model for the professional profile of a Data Scientist and evaluates the representativeness of this profile in two commonly recognized competences/skills frameworks in the field of Information and Communications Technology (ICT), namely in the European e-Competence (e-CF) framework and the Skills Framework for the Information Age (SFIA). The results indicate that a significant part of the knowledge base and skills set of Data Scientists are related with ICT competences/skills, including programming, machine learning and databases. The Data Scientist professional profile has an adequate representativeness in these two frameworks, but it is mainly seen as a multi-disciplinary profile, combining contributes from different areas, such as computer science, statistics and mathematics.por
dc.description.sponsorshipThis work was supported by COMPETE: POCI-01-0145-FEDER007043 and FCT − Fundação para a Ciência e Tecnologia, within the Project UID/CEC/00319/2013 (ALGORITMI). This work has also been funded by the SusCity project (MITP-TB/CS/0026/2013) and by Portugal Incentive System for Research and Technological Development, Project in co-promotion n° 002814/2015 (iFACTORY 2015-2018).por
dc.language.isoengpor
dc.publisherElsevier 1por
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5665-PICT/137220/PTpor
dc.rightsrestrictedAccesspor
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/por
dc.subjectConceptual modelpor
dc.subjectData sciencepor
dc.subjectData scientistpor
dc.subjectKnowledgepor
dc.subjectSkillspor
dc.titleThe data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information agepor
dc.typearticlepor
dc.peerreviewedyespor
oaire.citationStartPage726por
oaire.citationEndPage734por
oaire.citationIssue6por
oaire.citationVolume37por
dc.identifier.eissn0143-6236-
dc.identifier.doi10.1016/j.ijinfomgt.2017.07.010por
dc.subject.fosCiências Naturais::Ciências da Computação e da Informaçãopor
dc.description.publicationversioninfo:eu-repo/semantics/acceptedVersionpor
dc.subject.wosScience & Technologypor
sdum.journalInternational Journal of Information Managementpor
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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