참고문헌
- Choi, Sanghee & Lee, Jae Yun (2020). A bibliometric analysis on research trends and multidisciplinarity of the journal of humanities. The Journal of Humanities, 41(3), 13-42. http://doi.org/10.22947/ihmju.2020.41.3.001
- Han, Sang Woo (2020). A study on design of data literacy model based on digital humanities. Journal of the Korean Society for Information Management, 37(1), 179-195. http://doi.org/10.3743/KOSIM.2020.37.1.179
- Jeong, Yoo Kyung (2020). An analysis on research trends of digital humanities. Journal of the Korean Society for Information Management, 37(2), 311-331. http://doi.org/10.3743/KOSIM.2020.37.2.311
- Kim, Hea-Jin (2020). The main path analysis of korean studies using text mining: based on SCOPUS literature containing 'Korea' as a keyword. Journal of the Korean Society for Information Management, 37(3), 253-274. http://doi.org/10.3743/KOSIM.2020.37.3.253
- Kim, Hye Young (2020). Analysis of data literacy in the core curriculum to improve students' 4C skills: communication, collaboration, critical thinking, and creativity. Korean Journal of General Education, 14(6), 147-159. https://doi.org/10.46392/kjge.2020.14.6.147
- Kim, Jae Yeon (2023). We Need Different Data: Data that Makes Difference, Data that Creates Opportunity. Seoul: Sejong Books.
- Kim, Ji Hyun (2018). A content analysis of research data management training programs at the university libraries in North America: focusing on data literacy competencies. Journal of the Korean Society for Information Management, 35(4), 7-36. http://doi.org/10.3743/KOSIM.2018.35.4.007
- Kim, Seulki & Kim, Taeyoung (2021). A study of the definition and components of data literacy for K-12 AI education. Journal of the Korean Association of information Education, 25(5), 691-704. http://doi.org/10.14352/jkaie.2021.25.5.691
- Lee, Jae Yun & Choi, Sanghee (2015). Discipline bias of document citation impact indicators: analyzing articles in Korean citation index. Journal of the Korean Society for Information Management, 32(4), 205-221. http://doi.org/10.3743/KOSIM.2015.32.4.205
- Lee, Jae Yun & Chung, EunKyung (2022). Introducing keyword bibliographic coupling analysis (KBCA) for identifying the intellectual structure. Journal of the Korean Society for Information Management, 39(1), 309-330. http://doi.org/10.3743/KOSIM.2022.39.1.309
- Lee, Jae Yun (2006). A novel clustering method for examining and analyzing the intellectual structure of a scholarly field. Journal of the Korean Society for Information Management, 23(4), 215-231. https://doi.org/10.3743/KOSIM.2006.23.4.215
- Lee, Jae Yun (2013). A comparison study on the weighted network centrality measures of tnet and WNET. Journal of the Korean Society for Information Management, 30(4), 241-264. http://doi.org/10.3743/KOSIM.2013.30.4.241
- Lee, Jae Yun (2020a). A new perspective on constructing data literacy sub-competencies. Proceedings of the 27th Annual Conference of the Korean Society for Information Management, 165-175. Available: https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002707039
- Lee, Jae Yun (2020b). Analyzing the Intellectual structure of school library researches with citation-weighted author profiling. Journal of the Korean Society for Library and Information Science, 54(2), 197-223. http://doi.org/10.4275/KSLIS.2020.54.2.197
- Lee, Jae Yun (2021). Considering some of the decision criteria in the intellectual structure analysis process. Proceedings of the 28th Annual Conference of the Korean Society for Information Management, 91-100. Available: https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002755669
- Lee, Jae Yun (n.d.). BACA (ver. 0.1.1) [Computer software].
- Lee, Jae Yun, Kim, Pan Jun, Kang, DaeShin, Kim Hee jung, Yu, So-Young, & Lee, Woo-Hyoung (2011). A bibliometric analysis on LED research. Journal of Information Management, 42(3), 1-26. https://doi.org/10.1633/JIM.2011.42.3.001
- Lee, Jeong-Mee (2019). Re-approach to the concept of data literacy and its application to library information services. Journal of the Korean Society for Library and Information Science, 53(1), 159-179. http://doi.org/10.4275/KSLIS.2019.53.1.159
- Lee, Woo-Hyoung, Seok, Yeong-Cheol, & Park, Jun-Cheul (2012). Detecting emerging technology to use social network analysis: focusing on mobile telecommunication. The Journal of Information Systems, 21(4), 109-132. https://doi.org/10.5859/KAIS.2012.21.4.109
- Yoo, Yeong Jun & Lee, Jae Yun (2020). A bibliometric study on the KCI listed theological journals. Journal of the Korean Biblia Society for Library and Information Science, 31(3), 5-27. http://doi.org/10.14699/kbiblia.2020.31.3.005
- Amodio, P. & Brugnano, L. (2014). Recent advances in bibliometric indexes and the paperrank problem. Journal of Computational and Applied Mathematics, 267, 182-194. https://doi.org/10.1016/j.cam.2014.02.018
- Batagelj, V. (2003). Efficient Algorithms for Citation Network Analysis. CoRR cs.DL/0309023. Available: http://arxiv.org/abs/cs.DL/0309023
- Coughlan, T. (2020). The use of open data as a material for learning. Educational Technology Research and Development, 68(1), 383-411. https://doi.org/10.1007/s11423-019-09706-y
- De Nooy, W., Mrvar, A., & Batagelj, V. (2018). Exploratory Social Network Analysis with Pajek: Revised and Expanded Edition for Updated Software. Cambridge University Press.
- Gray, J., Gerlitz, C., & Bounegru, L. (2018). Data infrastructure literacy. Big Data & Society, 5(2). https://doi.org/10.1177/2053951718786316
- Hummon, N. P. & Dereian, P. (1989). Connectivity in a citation network: the development of DNA theory. Social Networks, 11(1), 39-63. http://doi.org/10.1016/0378-8733(89)90017-8
- Kang, I., Choung, J. Y., Kang, D., & Park, I. (2021). Divergence of knowledge production strategies for emerging technologies between late industrialized countries: focusing on quantum technology. ETRI Journal, 43(2), 246-259. http://doi.org/10.4218/etrij.2019-0501
- Knight, S., Matuk, C., & DesPortes, K. (2022). Guest editorial: learning at the intersection of data literacy and social justice. Educational Technology & Society, 25(4), 70-79. Available: http://hdl.handle.net/10453/163405 10453/163405
- Koltay, T. (2015). Data literacy: in search of a name and identity. Journal of Documentation, 71(2), 401-415. https://doi.org/10.1108/JD-02-2014-0026
- Liu, J. S. & Lu, L. Y. (2012). An integrated approach for main path analysis: development of the hirsch index as an example. Journal of the American Society for Information Science and Technology, 63(3), 528-542. http://doi.org/10.1002/asi.21692
- Mandinach, E. B. & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30-37. https://doi.org/10.3102/0013189X12459803
- Mandinach, E. B., Friedman, J. M., & Gummer, E. S. (2015). How can schools of education help to build educators' capacity to use data? a systemic view of the issue. Teachers College Record, 117(4), 1-50. https://doi.org/10.1177/016146811511700404
- Marjanovic, U., Taibi, D., Cabral, P., Urbsiene, L., Kasaj, A., & Marques, S. M. (2022). Digital transformation missing ingredients: data literacy. In: Lalic, B., Gracanin, D., Tasic, N., Simeunovic, N. (eds) Proceedings on 18th international conference on industrial systems (IS 2020), 340-344. https://doi.org/10.1007/978-3-030-97947-8_45
- Page, L. (1999). The PageRank Citation Ranking: Bringing Order to the Web. Stanford InfoLab.
- Prado, J. C. & Marzal, M. A. (2013). Incorporating data literacy into information literacy programs: core competencies and contents. Libri, 63(2), 123-134. https://doi.org/10.1515/libri-2013-0010
- Sander, I. (2020). What is critical big data literacy and how can it be implemented?. Internet Policy Review, 9(2). https://doi.org/10.14763/2020.2.1479
- Schvaneveldt, R. W. (ed). (1990). Pathfinder Associative Networks: Studies in Knowledge Organization. Norwood, New Jersey: Ablex.
- Yu, D. & Sheng, L. (2021). Influence difference main path analysis: evidence from DNA and blockchain domain citation networks. Journal of Informetrics, 15(4), 101186. https://doi.org/10.1016/j.joi.2021.101186