Formation of Data Science Teams based on Scenario Characteristics
The objective of this research was to identify a set of attributes to characterize data science scenarios to assists in the formation of an accompanying data science team. The six scenario characteristics were developed in consultation with a Subject Matter Expert (SME) to identify the important asp...
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| Published in | Proceedings of the Human Factors and Ergonomics Society Annual Meeting Vol. 65; no. 1; pp. 535 - 540 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Los Angeles, CA
SAGE Publications
01.09.2021
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| Online Access | Get full text |
| ISSN | 2169-5067 1071-1813 1071-1813 2169-5067 |
| DOI | 10.1177/1071181321651048 |
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| Abstract | The objective of this research was to identify a set of attributes to characterize data science scenarios to assists in the formation of an accompanying data science team. The six scenario characteristics were developed in consultation with a Subject Matter Expert (SME) to identify the important aspects of a data science endeavor. Concurrently, a generalizable role by task matrix was developed that captures the high-level data science functions and potential team member roles. This matrix was based on the NATO data science process function definitions, linked to the U.S. Department of Labor social science work activities, and data science role definitions. The mapping of the characteristics to the role by task matrix results in guidelines for forming a data science team; an example scenario with its characteristics and proposed team design is described. This work suggests methods to customize team information for specific data science needs based on scenario attributes. |
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| AbstractList | The objective of this research was to identify a set of attributes to characterize data science scenarios to assists in the formation of an accompanying data science team. The six scenario characteristics were developed in consultation with a Subject Matter Expert (SME) to identify the important aspects of a data science endeavor. Concurrently, a generalizable role by task matrix was developed that captures the high-level data science functions and potential team member roles. This matrix was based on the NATO data science process function definitions, linked to the U.S. Department of Labor social science work activities, and data science role definitions. The mapping of the characteristics to the role by task matrix results in guidelines for forming a data science team; an example scenario with its characteristics and proposed team design is described. This work suggests methods to customize team information for specific data science needs based on scenario attributes. |
| Author | Eshelman-Haynes, Candace Handley, Holly A. H. |
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| Copyright | 2021 by Human Factors and Ergonomics Society |
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| References | Handley, Heacox 2005 Perez 2010 2006 Smallman, Cook, Beer, Lacson 2009 Creekmore, Muscella, Petrun 2008 2011 Handley, Sorber, Dunaway 2006 Handley, Kandemir 2013 Otto 2016 bibr9-1071181321651048 bibr21-1071181321651048 bibr13-1071181321651048 bibr10-1071181321651048 Handley H. (bibr8-1071181321651048) 2013 bibr4-1071181321651048 bibr2-1071181321651048 bibr6-1071181321651048 Perez-Ramirez M. (bibr16-1071181321651048) 2019 bibr15-1071181321651048 bibr19-1071181321651048 bibr17-1071181321651048 bibr14-1071181321651048 bibr20-1071181321651048 bibr5-1071181321651048 bibr1-1071181321651048 Stoffler R. (bibr11-1071181321651048) 2019 bibr12-1071181321651048 bibr7-1071181321651048 Blunt R. (bibr3-1071181321651048) 2018 bibr18-1071181321651048 |
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| Title | Formation of Data Science Teams based on Scenario Characteristics |
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