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The influence of the open-endedness of data on the data scientists’ work practice and occupational identity
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Wisnuwardani, Febriana (2022) The influence of the open-endedness of data on the data scientists’ work practice and occupational identity. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3927821
Abstract
Data scientists have emerged as the primary knowledge workers in the age of big data and AI. More research needs to focus on the actual work of data scientists in interacting with data. Data scientists are highly dependent on data, and data plays a significant role in shaping what data scientists do and who they are. The openness of data interpretation challenges data scientists to extract insights for their business clients. Therefore, this research focuses on studying the influence of the open-endedness of data on the data scientists’ work practices and occupational identity. This research aims to explain (1) how data scientists navigate the open-endedness of data to extract valuable insights and (2) how the open-endedness of data shapes their occupational identity. By conducting semi-structured interviews and participant observation, this research gains two key findings. First, data scientists navigate the openendedness of data by performing a validation process that consists of three phases: validating problems, validating data, and validating algorithms. In doing the validation, data scientists engage in the act of making judgements. Second, because of the need to constantly make judgements, there is a contradiction between the identity that data scientists enact and espouse. Data scientists espouse objectivity while enacting their subjective judgments. This research contributes to the literature about data scientists, particularly their work practice and occupational identity.
Item Type: | Thesis (PhD) | ||||
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Subjects: | H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HF Commerce Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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Library of Congress Subject Headings (LCSH): | Information scientists, Identity (Psychology), Big data, Employees -- Attitudes, Occupations -- Research | ||||
Official Date: | December 2022 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Warwick Business School | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Oborn, Eivor ; Constantinides, Panos ; Gkeredakis, Manos | ||||
Sponsors: | Warwick Business School | ||||
Format of File: | |||||
Extent: | x, 189 pages : illustrations | ||||
Language: | eng |
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