A Text Analysis of Data Science Career Opportunities and U.S. iSchool Curriculum

Autor/in	Durr, Angel Krystina
Titel	A Text Analysis of Data Science Career Opportunities and U.S. iSchool Curriculum
Quelle	(2018), (123 Seiten) PDF als Volltext Verfügbarkeit Ph.D. Dissertation, University of North Texas
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	978-0-4388-7909-6
Schlagwörter	Hochschulschrift; Dissertation; Library Schools; Information Science; Information Science Education; Data; Careers; Employment Opportunities; Occupational Information + Suchen Sie Ihr Suchwort? Thesis; Dissertations; Academic thesis; Informationswissenschaft; Informationstechnologische Bildung; Daten; Career; Karriere; Berufschance; Beschäftigungschance; Berufsinformation
Abstract	Data science employment opportunities of varied complexity and environment are in growing demand across the globe. Data science as a discipline potentially offers a wealth of jobs to prospective employees, while traditional information science-based roles continue to decrease as budgets get cut across the U.S. Since data is related closely to information historically, this research will explore the education of U.S. iSchool professionals and compare it to traditional data science roles being advertised within the job market. Through a combination of latent semantic analysis of over 1600 job postings and iSchool course documentation, it is our aim to explore the intersection of library and information science and data science. Hopefully these research findings will guide future directions for library and information science professionals into data science driven roles, while also examining and highlighting the data science techniques currently driven by the education of iSchool professionals. In addition, it is our aim to understand how data science could benefit from a mutually symbiotic relationship with the field of information science as statistically data scientists spend far too much time working on data preparation and not nearly enough time conducting scientific inquiry. The results of this examination will potentially guide future directions of iSchool students and professionals towards more cooperative data science roles and guide future research into the intersection between iSchools and data science and possibilities for partnership. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01