Browse > Article
http://dx.doi.org/10.16981/kliss.53.2.202206.305

Degree Programs in Data Science at the School of Information in the States  

Park, Hyoungjoo (충남대학교 문헌정보학과)
Publication Information
Journal of Korean Library and Information Science Society / v.53, no.2, 2022 , pp. 305-332 More about this Journal
Abstract
This preliminary study examined the degree programs in data science at the School of Information in the States. The focus of this study was the data science degrees offered at the School of Information awarded by the 64 Library and Information Science (LIS) programs accredited by the American Library Association (ALA) in 2022. In addition, this study examined the degrees, majors, minors, specialized tracks, and certificates in data science, as well as the potential careers after earning a data science degree. Overall, eight Schools of Information (iSchools) offered 12 data science degrees. Data science courses at the School of Information focus on topics such as introduction to data science, information retrieval, data mining, database, data and humanities, machine learning, metadata, research methods, data analysis and visualization, internship/capstone, ethics and security, user, policy, and curation and management. Most schools did not offer traditional LIS courses. After earning the data science degree in the School of Information, the potential careers included data scientists, data engineers and data analysts. The researcher hopes the findings of this study can be used as a starting point to discuss the directions of data science programs from the perspectives of the information field, specifically the degrees, majors, minors, specialized tracks and certificates in data science.
Keywords
Data Science; Degree Programs in Data Science; LIS Curriculum; Curriculum Development;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
1 Bae, Jinhee, Kim, Kyoung Huy, Kim, Keunkon, Seo, Hye Seok, & Lee, Jeong Mee (2012). A study on effectiveness of project learning in social welfare education. Korean Journal of Social Welfare Education, 18, 1-22.
2 Bae, Jinhee, Kim, Se Ryeong, & Jung, Jaemin (2021). A study on the development of convergence subjects to improve social problem solving ability. Korean Journal of Social Welfare Education, 56, 131-157. https://doi.org/10.31409/KJSWE.2021.56.131   DOI
3 Chang, Youngjae (2017). The direction of data science education in the fourth industrial revolution era: focusing on understanding of artificial intelligence and data initiative. The Journal of Integrated Humanities, 9(10), 155-180.
4 Cho, Wooje & Yu, Mi Rim (2018). Creating value for education through big data analysis education programs. The Korea Journal of Big Data, 3(2), 123-130. https://doi.org/10.36498/kbigdt.2018.3.2.123   DOI
5 Jang, Duk-Hyun (2015). iSchool movement: a critical discourse analysis. Journal of Korean Library and Information Science Society, 46(1), 135-154. https://doi.org/10.16981/kliss.46.1.201503.135   DOI
6 Jung, Seungwha & Do, Jaewoo (2019). A case study on operation of big data educational program. Journal of Education & Culture, 25(5), 621. https://doi.org/10.24159/joec.2019.25.5.621   DOI
7 Stanton, J. M. (2012). Data science: what's in it for the new librarian? Available: https://ischool.syr.edu/data-science-whats-in-it-for-the-new-librarian/
8 Tang, R. & Sae-Lim, W. (2017). Data science programs in U.S. higher education: an interview with the authors. Journal of eScience Librarianship, 6(1), e1105. https://doi.org/10.7191/jeslib.2017.1105   DOI
9 Lee, Hee Yong (2020). A study on the present state of convergence curriculum and convergence methodology: in humanities, social sciences and arts. Korean Journal of Arts Education, 18(4), 135-154.
10 Kim, Yongmin (2018). Data Science Education Program to Improve Computational Thinking and Creativity. Doctoral dissertation, Jeju National University. Republic of Korea.
11 Lee, Hyewon & Han, Seunghee (2020). An analysis of data science curriculum in Korea. Journal of the Korean Society for Library and Information Science, 54(1), 365-385. https://doi.org/10.4275/KSLIS.2020.54.1.365   DOI
12 Leem, Jung-Hoon (2020). A study on the educational applicability of team teaching for facilitating convergence education in higher education. Journal of Educational Innovation Research, 30(3), 23-51. https://doi.org/10.21024/pnuedi.30.3.202009.23   DOI
13 Park, Jiin & Park, Ji-Hong (2021). A study on the job duties and competencies of data librarians: using job advertisement analysis in the United States. Journal of the Korean Biblia Society for Library and Informaton Science, 32(3), 145-162. https://doi.org/10.14699/kbiblia.2021.32.3.145   DOI
14 Indiana University Purdue University - Indiannapolis [n.d.]. Data Science B.S. (online) + applied data science M.S. Available: https://soic.iupui.edu/degrees/accelerated-bachelors-masters/data-science-ads
15 Park, Hyoungjoo (2022b). An examination of the course syllabi related to data science at the ALA-accredited library and information science programs. Journal of the Korean Society for Information Management, 39(1), 119-143. https://doi.org/10.3743/KOSIM.2022.39.1.119   DOI
16 Youn, Jin Young, Kim, Yu Mi, So, Jae Hwan, & Kim, Yeon Hyeoung (2019). A study on the media art STEAM education program using data science and artificial intelligence. The Korean Society of Science & Art, 37(5), 265-276. https://doi.org/10.17548/ksaf.2019.12.30.265   DOI
17 Brady, E. H. (2019). The challenge of big data and data science. Annual Review of Political Science, 22, 297-323. https://doi.org/10.1146/annurev-polisci-090216-023229   DOI
18 Ministry of Science and ICT & Korea Data Agency (2022). A summary of the main results of the study on the status of the data industry in 2021. Available: https://www.kdata.or.kr/kr/board/info_01/boardView.do?bbsIdx=33172
19 Park, Hyoungjoo (2022a). An examination of core competencies for data librarians. Journal of the Korean Biblia Society for Library and Information Science, 33(1), 301-319. https://doi.org/10.14699/kbiblia.2022.33.1.301   DOI
20 Griffith, B. C. (1980). Key Papers in Information Science. New York: White Plains.
21 Kim, J., Warga, E., & Moen, W. (2013). Competencies required for digital curation: an analysis of job advertisements. International Journal of Digital Curation, 66-83. https://doi.org/10.2218/ijdc.v8i1.242   DOI
22 Zawadzki, K. (2014). Is data science a buzzword? Available: https://mywebvault.wordpress.com/2017/05/18/is-data-science-a-buzzword-modern-data-scientist-defined-marketing-distillery/
23 University of Michigan (2022). Career and salary information. Available: https://www.si.umich.edu/employers/career-and-salary-information#:~:text=In%20recent%20rankings%2C%20U%2DM%20schools,satisfaction%20(95%25%20overall)
24 Wang, L. (2018). Twinning data science with information science in schools of library and information science. Journal of Documentation, 74(6), 1243-1257. https://doi.org/10.1108/JD-02-2018-0036   DOI
25 Zhu, Y. & Xiong, Y. (2015). Towards data science. Data Science Journal, 14(8), 1-7. https://doi.org/10.5334/dsj-2015-008   DOI
26 Robinson, L. (2009). Information science: communication chain and domain analysis. Journal of Documentation, 65(4), 578-591. https://doi.org/10.1108/00220410910970267   DOI
27 Cervone, H. F. (2015). Informatics and data science: an overview for the information professional. Digital Library Perspectives, 32(1), 7-10. https://doi.org/10.1108/DLP-10-2015-0022   DOI
28 Semeler, A., Pinto, A., & Rozados, H. (2019). Data science in data librarianship: core competencies of a data librarian. Journal of Librarianship and Information Science, 51(3), 771-780. https://doi.org/10.1177/0961000617742465   DOI
29 Syracuse University [n.d.]. Career outlook. Available: https://ischool.syr.edu/careers/career-outlook
30 University of Illinois - Urbana Champaign [n.d.-b]. BS in Information Science + Data Science. Available: https://ischool.illinois.edu/degrees-programs/undergraduate/bs-data-science
31 University of Illinois - Urbana Champaign [n.d.-a]. iSchool illini success 2018-2020. Available: https://ischool.illinois.edu/sites/default/files/documents/MSLIS%20first%20desti nations%202018-20.pdf
32 SungKyunKwan University (2019). Convergence major in data science (school year 2019). Available: https://lis.skku.edu/lis/community/under_notice.do?mode=download&articleNo=50833&attachNo=35390
33 Lyon, L., Mattern, E., Acker, A., & Langmead, A. (2015). Applying translational principles to data science curriculum. Proceedings of the iPres. Chapel Hill. Available: http://d-scholarship.pitt.edu/id/eprint/27159
34 Harris-Pierce, R. L. & Liu, Y. Q. (2012). Is data curation education at library and information science schools in North America adequate? New Library World, 113(11/12), 598-613. https://doi.org/10.1108/03074801211282957   DOI
35 Burton, M. & Lyon, L. (2017). Data science in libraries. Bulletin of the Association for Information Science and Technology, 43(4), 33-35. https://doi.org/10.1002/bul2.2017.1720430409   DOI
36 Kang, Ji Hei (2016). Study on the current status of data science curriculum in library and information science and its direction. Journal of Korean Library and Information Science Society, 47(3), 343-363. https://doi.org/10.16981/kliss.47.3.201609.343   DOI
37 Kim, Hyo-Jung & Kim, Hee-Woong (2021). A curriculum study to strengthen AI and data science job competency. Information Policy, 28(2), 34-56. https://do.org/10.22693/NIAIP.2021.28.2.034   DOI
38 Kim, Misung, Choi, Myoungsook, & Lee, Sung-Ha (2021). An analysis of domestic research trends on university convergence education: focusing on academic papers published in registered journals from 2011 to 2020. The Korean Journal of Educational Methodology Studies, 33(1), 77-99. https://doi.org/10.17927/tkjems.2021.33.1.77   DOI
39 Ministry of Science and ICT (2022, January 27). (4th revision) Announcement of integration of new tasks for nurturing scientific and technological innovation talents in 2022. Available: https://www.msit.go.kr/bbs/view.do?sCode=user&mId=129&mPid=128&bbsSeqNo=100&nttSeqNo=3177549
40 Yi, Myongho (2016). A study on the curricullum of data science. Journal of the Korean Biblia Society for library and Information Science, 27(1), 263-290. https://doi.org/10.14699/kbiblia.2016.27.1.263   DOI
41 American Library Association. (2022, March 25). Directory of institutions offering ALA-accredited master's programs in library and information studies. Available: https://www.ala.org/educationcareers/accreditedprograms/directory
42 Executive Office of the President (2016). The federal big data research and development strategic plan. Available: https://www.nitrd.gov/PUBS/bigdatardstrategicplan.pdf
43 Anselmo, J. (2021). A social science major is coming to UMD in fall 2022. Available: https://dbknews.com/2021/04/25/a-social-data-science-major-is-coming-to-umd-in-fall-2022/
44 Bush, V. (1945). As we may think. Atlantic Monthly, 176(1), 101-108.
45 Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64. https://doi.org/10.1145/2500499   DOI
46 Li, S., Zhuang, X., Xing, W., & Guo, W. (2013). The cultivation of scientific data specialists: development of LIS education oriented e-science service requirements. Library Hi Tech, 31(4), 700-724. https://doi.org/10.1108/LHT-06-2013-0070   DOI
47 Indiana University Purdue University - Indianapolis (2021). Available: https://tableau.bi.iu.edu/t/prd/views/FirstDestination2016/CareerOutcomesGroup?iframeSizedToWindow=true&%3Aembed=y&%3AshowAppBanner=false&%3Adisplay_count=no&%3AshowVizHome=no#1#1
48 iSchools Inc. (2022). Directory. Available: https://ischools.org/Directory
49 Kellam, L. & Thompson, K. (2016). Introduction to Databrarianship: the Academic Data Librarian in Theory and Practice. Chicago, IL: Association of College and Research Libraries.
50 Lyon, L. & Brenner, A. (2015). Bridging the data talent gap: positioning the iSchool as an agent for change. International Journal of Digital Curation, 10(1), 111-122. https://doi.org/10.2218/ijdc.v10i1.349   DOI
51 Macelil, M. (2015). Creating tomorrow's technologists: contrasting information technology curriculum in north American library and information science graduate programs against Code4lib job listings. Journal of Education for Library and Information Science, 56(3), 198-212. https://doi.org/10.3138/jelis.56.3.198   DOI
52 Shi, Y., Yu, P. S., Zhu, Y., & Tian, Y. (2014). Explore new field of data science under big data era: preface for ICDS 2014. Procedia Computer Science, 30, 1-3. https://doi.org/10.1016/j.procs.2014.05.374   DOI
53 Lee, Hee Yong, Yoon, Ahyoung, & Kim, Jae-Deuk (2014). A study on the present state of humanities and arts convergence education in Korean universities. Studies in Humanities and Social Sciences, 44, 183-222. https://doi.org/10.17939/hushss.2014..44.007   DOI