Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.
%0 Journal Article
%1 zhang_data_2022
%A Zhang, Y.
%A Wu, D.
%A Hagen, L.
%A Song, I.-Y.
%A Mostava, J.
%A Oh, S.
%A Anderson, T.
%A Shah, C.
%A Bishop, B. W.
%A Hopfgartner, F.
%A Eckert, K.
%A Federer, L.
%A Saltz, J. S.
%D 2022
%J Journal of the American Society for Information Science. American Society for Information Science
%K data_science
%T Data science curriculum in the iField
%U https://eprints.whiterose.ac.uk/188812/
%X Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.
@article{zhang_data_2022,
abstract = {Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.},
added-at = {2022-09-27T11:36:02.000+0200},
author = {Zhang, Y. and Wu, D. and Hagen, L. and Song, I.-Y. and Mostava, J. and Oh, S. and Anderson, T. and Shah, C. and Bishop, B. W. and Hopfgartner, F. and Eckert, K. and Federer, L. and Saltz, J. S.},
biburl = {https://www.bibsonomy.org/bibtex/28f37691987f456e1b6dbe65bcc136954/lepsky},
copyright = {cc\_by\_nc\_nd\_4},
interhash = {2cab4e679b0ae10bd077a4ee7887d8bb},
intrahash = {8f37691987f456e1b6dbe65bcc136954},
issn = {0002-8231},
journal = {Journal of the American Society for Information Science. American Society for Information Science},
keywords = {data_science},
language = {en},
month = jul,
note = {Publisher: Association for Information Science and Technology (ASIS\&T)},
timestamp = {2022-09-27T11:41:21.000+0200},
title = {Data science curriculum in the {iField}},
url = {https://eprints.whiterose.ac.uk/188812/},
urldate = {2022-09-07},
year = 2022
}