Following is an annotated bibliography that helps to broaden the context of the issues and concepts discussed by FLC members.
Teaching and Learning.
Mellody, M., & National Research Council. (2014). Training students to extract value from big data: Summary of a workshop. Washington, District of Columbia: National Academies Press. Retrieved from https://ezproxy.mtsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=941883&site=eds-live&scope=site
This in-depth report describes and recommends training for students in the use of big data. The report primarily focuses on the need for training, principles for working with big data, and data science curricula. The authors place a special focus on the discussion of the …show more content…
Burton, M., Lyon, L., Erdmann, C. & Tijerina, B. (2018). Shifting to data savvy: The future of data science in libraries. Retrieved from http://d-scholarship.pitt.edu/33891/
This report is an outcome of an program funded by the Institute for Museum and Library Services called the “Data Science in Libraries Project”. The authors detail drivers of change, barriers to change, and recommendations. Libraries are well-positioned to provide resources and services for data science in general, and open data specifically. Library and University leaders need to provide support structures to facilitate librarians’ acquisition of new skills, while piloting data science services with partners and stakeholders on campus and beyond.
Maxwell, D., Norton, H., & Wu, J. (2018). The data science opportunity: Crafting a holistic strategy. Journal of Library Administration, 58(2), 111-127. 10.1080/01930826.2017.1412704 Retrieved from https://ezproxy.mtsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=lxh&AN=127699139&site=eds-live&scope=site
The authors frame new methods of data intensive research as a paradigm shift in scientific discovery. The authors define the scope of the issues facing libraries, analyze how libraries in general have responded, and include the results of the faculty survey about needs for support and training in data science
Teaching and Learning.
Mellody, M., & National Research Council. (2014). Training students to extract value from big data: Summary of a workshop. Washington, District of Columbia: National Academies Press. Retrieved from https://ezproxy.mtsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=941883&site=eds-live&scope=site
This in-depth report describes and recommends training for students in the use of big data. The report primarily focuses on the need for training, principles for working with big data, and data science curricula. The authors place a special focus on the discussion of the …show more content…
Burton, M., Lyon, L., Erdmann, C. & Tijerina, B. (2018). Shifting to data savvy: The future of data science in libraries. Retrieved from http://d-scholarship.pitt.edu/33891/
This report is an outcome of an program funded by the Institute for Museum and Library Services called the “Data Science in Libraries Project”. The authors detail drivers of change, barriers to change, and recommendations. Libraries are well-positioned to provide resources and services for data science in general, and open data specifically. Library and University leaders need to provide support structures to facilitate librarians’ acquisition of new skills, while piloting data science services with partners and stakeholders on campus and beyond.
Maxwell, D., Norton, H., & Wu, J. (2018). The data science opportunity: Crafting a holistic strategy. Journal of Library Administration, 58(2), 111-127. 10.1080/01930826.2017.1412704 Retrieved from https://ezproxy.mtsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=lxh&AN=127699139&site=eds-live&scope=site
The authors frame new methods of data intensive research as a paradigm shift in scientific discovery. The authors define the scope of the issues facing libraries, analyze how libraries in general have responded, and include the results of the faculty survey about needs for support and training in data science