The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age
The 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 artifa...
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Veröffentlicht in: | International journal of information management 2017-12, Vol.37 (6), p.726-734 |
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description | The 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 increased 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. |
doi_str_mv | 10.1016/j.ijinfomgt.2017.07.010 |
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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 increased 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. 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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 increased 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.</description><subject>Applications programs</subject><subject>Artificial intelligence</subject><subject>Ciências da Computação e da Informação</subject><subject>Ciências Naturais</subject><subject>Communications technology</subject><subject>Conceptual model</subject><subject>Data science</subject><subject>Data scientist</subject><subject>Expert systems</subject><subject>Information management</subject><subject>Information technology</subject><subject>Knowledge</subject><subject>Knowledge bases (artificial intelligence)</subject><subject>Machine learning</subject><subject>Science & Technology</subject><subject>Scientists</subject><subject>Skills</subject><issn>0268-4012</issn><issn>1873-4707</issn><issn>0143-6236</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFUcuKFDEUDaJgO_oNBlxXe5NUJanl0IwPGHAzrkMqdWtMTVdSJukWP8J_NtUt4k64kMV53HtOCHnLYM-Ayffz3s8-THF5LHsOTO2hDoNnZMe0Ek2rQD0nO-BSNy0w_pK8ynmGSoSO78ivh29IR1sszc5jKD4XuqY4-SNSG0bqS6YJ14S5grb4MwbMmfpASxXenVJc0QaKzSEuKxYMDumU7II_Ynq6OGy8_OSPx_wPMMV0AbbD01J9Y6D2EV-TF5M9Znzz570hXz_cPRw-NfdfPn4-3N43TkhdGj2Kvhu44NI5NzHFXa_7th9HWdMOA3IBney0QFC9ljC5HoR1uu1xmFw3KHFD3l19a9TvJ8zFzPGUQl1pOLS6E7xTsrLUleVSzDnhZNbkF5t-GgZm697M5m_3ZuveQB0GVUmvyuSsXU3Cc-3VZsM056aVQm-U2ysFa86zx2QuH-Bw9AldMWP0_13zG5zsns8</recordid><startdate>20171201</startdate><enddate>20171201</enddate><creator>Costa, Carlos</creator><creator>Santos, Maribel Yasmina</creator><general>Elsevier Ltd</general><general>Elsevier</general><general>Elsevier Science Ltd</general><scope>RCLKO</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>E3H</scope><scope>F2A</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20171201</creationdate><title>The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age</title><author>Costa, Carlos ; Santos, Maribel Yasmina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-8d395b2326cccf172c98949dd6470bbe23056583e079860fc903ac849ebfc5b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Applications programs</topic><topic>Artificial intelligence</topic><topic>Ciências da Computação e da Informação</topic><topic>Ciências Naturais</topic><topic>Communications technology</topic><topic>Conceptual model</topic><topic>Data science</topic><topic>Data scientist</topic><topic>Expert systems</topic><topic>Information management</topic><topic>Information technology</topic><topic>Knowledge</topic><topic>Knowledge bases (artificial intelligence)</topic><topic>Machine learning</topic><topic>Science & Technology</topic><topic>Scientists</topic><topic>Skills</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Costa, Carlos</creatorcontrib><creatorcontrib>Santos, Maribel Yasmina</creatorcontrib><collection>RCAAP open access repository</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of information management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Costa, Carlos</au><au>Santos, Maribel Yasmina</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age</atitle><jtitle>International journal of information management</jtitle><date>2017-12-01</date><risdate>2017</risdate><volume>37</volume><issue>6</issue><spage>726</spage><epage>734</epage><pages>726-734</pages><issn>0268-4012</issn><eissn>1873-4707</eissn><eissn>0143-6236</eissn><abstract>The 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 increased 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). 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subjects | Applications programs Artificial intelligence Ciências da Computação e da Informação Ciências Naturais Communications technology Conceptual model Data science Data scientist Expert systems Information management Information technology Knowledge Knowledge bases (artificial intelligence) Machine learning Science & Technology Scientists Skills |
title | The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age |
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