The Development of Data Science Education in China from the LIS Perspective
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Keywords

data science education
LIS programs
education of LIS
curriculum

How to Cite

Zhang, J., Fu, A., Wang, H., & Yin, S. (2017). The Development of Data Science Education in China from the LIS Perspective. International Journal of Librarianship, 2(2), 3–17. https://doi.org/10.23974/ijol.2017.vol2.2.29
Received 2017-06-16
Accepted 2017-09-26
Published 2017-12-15

Abstract

The aim of this paper is to introduce the development of data science in higher education in China, including the policy and educational programs at various levels. We investigated the data science education of five LIS (Library and Information Studies) schools in China, using Fudan University’s Data Management and Application Master’s Program as an example for more specific information about the curriculum structure, course focus and teaching methods in data science education. The paper further describes the action of promoting data science and data science education in the field of LIS by the China Academic Library Research Data Management Implementation Group.
https://doi.org/10.23974/ijol.2017.vol2.2.29
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References

Aasheim, C. L., Williams, S., Rutner, P., & Gardiner, A. (2015). Data analytics vs. data science: a study of similarities and differences in undergraduate programs based on course descriptions. Journal of Information Systems Education, 26(2), 103-115.

Bai, H. (2016). Expert predicted: The shortage of data talent in China is about a million and a half. Retrieved from http://news.cyol.com/content/2016-05/30/content_12687384.htm. [in Chinese]

Bauman, P. T., Chandola, V., Patra, A., Jones, M. (2014). Development of a computational and data-enabled science and engineering Ph.D. program. 2014 Workshop on Education for High Performance Computing (EduHPC), New Orleans, Louisiana. November 16-21, 2014. Piscataway, NJ, USA: IEEE Press. doi:10.1109/EduHPC.2014.8

Baumer, B. (2015). A data science course for undergraduates: Thinking with data. American Statistician, 69(4), 334-342.

Bichler, M., Heinzl, A., & Aalst, W. M. P. V. D. (2017). Business analytics and data science: Once again? Business & Information Systems Engineering, 59(2),1-3. doi: https://doi.org/10.1007/s12599-016-0461-1

Cao, R., Wang, Q., Geng, Q., & Liu, X. (2016). Investigation and analysis of data curation education in foreign universities. Library and Information Service, (4), 52-58. doi:10.13266/j.issn.0252-3116.2016.04.007. [in Chinese]

Chen, H. & Zhang, Y., (2017). Educating data management professionals: A content analysis of job descriptions. The Journal of Academic Librarianship, 43(1), 18-24. doi:http://dx.doi.org/10.1016/j.acalib.2016.11.002

Chen, Z., & He, T. (2016). Data science: The demand and development of talents. Big data research, 5, 95-106. [in Chinese]

China Academic Degree & Graduate Education Development Centre & Ministry of Education of the People’s Republic of China. (2009). Regulation of establishment and management in degree granting and talents-nurturing discipline catalogue. Retrieved May 6, 2017, from http://old.moe.gov.cn//publicfiles/business/htmlfiles/moe/moe_834/200903/45419.html. [in Chinese]

Department for Business, Innovation & Skills. (2013). Seizing the data opportunity: A strategy for UK data capability. Retrieved from https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/254136/bis-13-1250-strategy-for-uk-data-capability-v4.pdf

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.

Heidorn, P., Palmer, C., Cragin, M., & Smith, L. (2007). Data curation education and biological information specialists. In DigCCurr 2007: An international symposium in digital curation. Chapel Hill, NC, April 18-20, 2007. Retrieved from http://www.ils.unc.edu/digccurr2007/papers/heidornEtal_paper_8-2.pdf

Huang, R & J, C. (2015). Current situation and enlightenment of the data curation education in University of Illinois at Urbana-Champaign. Library & Information, 1, 61-65. doi:10.11968/tsygb.1003-6938.2015010. [in Chinese]

Kirkpatrick, K. (2015). Putting the data science into journalism. Communications of the ACM, 58(5), 15-17. doi: 10.1145/2742484

Liu, B. & Jia, Y. (2015). Cultivating talents in the age of big data in Japan: Background, research direction, plan and measures. E-Government, (10), 85-95. doi: 10.16582/j.cnki.dzzw.2015.10.012. [in Chinese]

Ma, H. & Pu, P. (2016). The pondering of cultivation for talents in data under the circumstance of big data in China. Digital Library Forum, (1), 2-9. [in Chinese]

Macmillan, D. (2015). Developing data literacy competencies to enhance faculty collaborations. Liber Quarterly the Journal of European Research Libraries, 24(3), 140-160. doi: 10.18352/lq.9868

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., & Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity. Retrieved from http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation

Ministry of Education of the People’s Republic of China. (2017a). Notice to the 2016 approved majors at undergraduate level by the Ministry of Education of the People’s Republic of China. Retrieved May 6, 2017, from http://www.moe.edu.cn/srcsite/A08/moe_1034/s4930/201703/t20170317_299960.html. [in Chinese]

Ministry of Education of the People’s Republic of China. (2017b). Accelerate the transformation of administration and service in higher education. Retrieved May 6, 2017, from http://www.moe.gov.cn/jyb_xwfb/s271/201704/t20170406_301996.html. [in Chinese]

Ministry of Education of the People's Republic of China (2016) Ministry of Education of the People's Republic of China’s reply to the advice NO.2174 of the fourth session of the 12th NPC. Retrieved May 6, 2017, from http://www.moe.edu.cn/jyb_xxgk/xxgk_jyta/jyta_gaojiaosi/201611/t20161102_287366.html. [in Chinese]

Ministry of Education of the People’s Republic of China. (2015). Catalogue Of university diplomatic education majors (2015). Retrieved May 6, 2017, from: http://www.moe.edu.cn/srcsite/A07/moe_953/201511/t20151105_217877.html. [in Chinese]

National Science Library of China Academy of Sciences (2017). The description of postgraduate programs in LIS of National Science Library, China Academy of Sciences. Retrieved May 6, 2017, from http://www.las.cas.cn/yjsjy/pyyxw/pyfa/201704/U020170406457750783870.pdf. [in Chinese]

Qin, J., & D’Ignazio, J. (2010). Lessons learned from a two-year experience in science data literacy education. International Association of Scientific and Technological University Libraries, 31st Annual Conference, 188–204. Retrieved from http://docs.lib.purdue.edu/iatul2010/conf/day2/5

Qin, J. & D’Ignazio, J. (2016). Enhancing scientific data literacy in college students: Experience and lessons learned. Journal of Librarianship & .Information Studies, 8(1), 1-27. doi: 10.6575/JILA.2016.88.01

Ramamurthy, B. (2016). A practical and sustainable model for learning and teaching data science. SIGCSE '16 Proceedings of the 47th ACM Technical Symposium on Computing Science Education. Memphis, Tennessee, USA. March 2-5, 2016. New York, NY, USA: ACM. doi: 1145/2839509.2844603

School of Information Resources Management, Renmin University of China (2016). Undergraduate programs. Received from School of Information Resources Management, Renmin University of China website, Retrieved May 6, 2017, from http://irm.ruc.edu.cn/more.php?cid=234. [in Chinese]

School of Information Management of Nanjing University (2015). Academic research and scientific innovation. Received from School of Information Management of Nanjing University website, Retrieved May 6, 2017, from http://im.nju.edu.cn/content.do?mid=6&mmid=66. [in Chinese]

Shen, H., Tan, H., & Wen, L. (2014). Data literacy of data journalists. Youth Journalist (21).17-18. doi: 10.15997/j.cnki.qnjz.2014.21.014. [in Chinese]

Si, L., Xing, W., Guo, W., & Zhuang, X. (2013). The cultivation of scientific data specialists. Library Hi Tech, 31(4), 700-724. doi: https://doi.org/10.1108/LHT-06-2013-0070

Song, I., & Zhu, Y. (2016). Big data and data science: what should we teach? Expert Systems, 33(4), 364-373. doi:10.1111/exsy.12130

Stephenson, E., & Caravello, P. S. (2007). Incorporating data literacy into undergraduate information literacy programs in the social sciences: A pilot project. Reference Services Review, 35(4), 525-540. doi: https://doi.org/10.1108/00907320710838354

Sun, X. & Yin, B. (2017). Statistics in the context of big data age. Statistics & Decision, 6, 2+189. [in Chinese]

Tang, R & Sae-Lim, W. (2016). Data science programs in U.S. higher education: An exploratory content analysis of program description, curriculum structure, and course focus. Education for Information, 32(3), 269-290

Tonta, Y. (2016). Developments in education for information: Will “data" trigger the next wave of curriculum changes in LIS schools? Pakistan Journal of Information Management & Libraries, 17, 2-12. Retrieved from: http://yunus.hacettepe.edu.tr/~tonta/yayinlar/tonta-pakistan-jiml-2016-888-2369-1-SM.pdf

Veaux, R., Agarwal, M., Averett, M., Baumer, B.S., Bray, A., Bressoud, T. C., …Tiruviluamala, N., Uhlig, P., Washington, T. M., Wesley, C. L., White, D., & Ye, P. (2017). Curriculum guidelines for undergraduate programs in data science. Annual Review of Statistics and Its Application, 4(1), 15-30. Retrieved from: http://www.stat.berkeley.edu/~nolan/Papers/Data.Science.Guidelines.16.9.25.pdf

Wang, C. Y. (2015). Survey report on MLIS program development in China (Master thesis). Available from CNKI Master’s Theses database. Retrieved from http://xueshu.baidu.com/s?wd=paperuri%3A%28481f34b67597895200f1fd0c92abdfc6%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fcdmd.cnki.com.cn%2FArticle%2FCDMD-10269-1016126721.htm&ie=utf-8&sc_us=2266641113642335464. [in Chinese]

Wang, H., Gao, H., Yin, S., & Zhu, J. (2017). The design of course architecture for big data, Proceedings of the ACM Turing 50th Celebration Conference- China (ACM TUR-C '17). Shanghai, China. May 12-14, 2017. New York, NY: ACM.

Wang, X, & Liu, H. (2016). Importance of application of data science in experimental teaching of data science in experimental teaching of economics and management specialty. Experimental Technology and Management, 33(4), 179-181. [in Chinese]

Yu, W. (2017). Editors’ big data literacy. China Publishing Journal, (5), 12-16. [in Chinese]

Zhang, H & Huang, S. (2014).Approaches to develop big data analysis ability of students in Statistics. Statistics and Decision, 24, 66-68. [in Chinese]

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