Shalini R. Urs and Minhaj, Mohamed (2023) Evolution of data science and its education in iSchools: An impressionistic study using curriculum analysis. Journal of the Association for Information Science and Technology, 74 (6). pp. 606-622. ISSN 2330-1643
Full text not available from this repository. (Request a copy)Abstract
Data Science (DS) has emerged from the shadows of its parents-statistics and computer science-into an independent field since its origin nearly six decades ago. Its evolution and education have taken many sharp turns. We present an impressionistic study of the evolution of DS anchored to Kuhn's four stages of paradigm shifts. First, we construct the landscape of DS based on curriculum analysis of the 32 iSchools across the world offering graduate-level DS programs. Second, we paint the ``field'' as it emerges from the word frequency patterns, ranking, and clustering of course titles based on text mining. Third, we map the curriculum to the landscape of DS and project the same onto the Edison Data Science Framework (2017) and ACM Data Science Knowledge Areas (2021). Our study shows that the DS programs of iSchools align well with the field and correspond to the Knowledge Areas and skillsets. iSchool's DS curriculums exhibit a bias toward ``data visualization'' along with machine learning, data mining, natural language processing, and artificial intelligence; go light on statistics; slanted toward ontologies and health informatics; and surprisingly minimal thrust toward eScience/research data management, which we believe would add a distinctive iSchool flavor to the DS.
Item Type: | Article |
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Subjects: | K Library and Information Science > Library and Information Science |
Divisions: | Department of > International School of Information Management |
Depositing User: | C Swapna Library Assistant |
Date Deposited: | 20 Jul 2023 07:00 |
Last Modified: | 20 Jul 2023 07:00 |
URI: | http://eprints.uni-mysore.ac.in/id/eprint/17656 |
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