Diving into Data: Developing Data Fluency for Librarians

As data services continue to emerge as a growth area for academic research libraries, many librarians are finding themselves in need of a skill upgrade in order to support research data at a level of excellence consistent with other library services. With the full support of its administrators, the University of Michigan (UM) Library has implemented a three-stage professional development program to develop readiness for data services within the organization. The first stage consists of a two-part workshop series presenting basic data concepts around data structures, storage, security, and sharing. These workshops build a shared understanding and vocabulary among librarians across the institution as a foundation for more specialized training. The second stage employs a workflow developed by UM librarians, the Deep Dive into Data, which provides a self-directed, iterative, non-linear method for exploring the data landscape around a particular research discipline. Deep Dive workshops apply this workflow to an example discipline through in-class exercises and discussion, providing librarians with an expert-mediated means to build their familiarity with the tool before applying it to their own work. The ongoing third stage addresses specific topics in research data which are broadly applicable across disciplines. Some of these workshops explore cross-disciplinary data techniques which librarians may encounter or recommend to researchers, such as text mining. Others connect librarians to services provided elsewhere on campus, such as data storage, by inviting colleagues from those providers to brief library staff on the basics of the service and how to make an effective referral. Another type expands traditional public services skills, such as reference interviews, into the data services realm by providing an overview of current best practices and reports from individual librarians who have been piloting these services. Feedback gathered from participants at each stage has informed planning for subsequent offerings.http://deepblue.lib.umich.edu/bitstream/2027.42/117590/1/Martin_Oehrli_Diving_Into_Data.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/117590/2/Martin_Oehrli_Table_1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/117590/3/Martin_Oehrli_Table_2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/117590/4/Martin_Oehrli_Appendix_A.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/117590/5/Martin_Oehrli_Appendix_B.pdfDescription of Martin_Oehrli_Diving_Into_Data.pdf : Chapter textDescription of Martin_Oehrli_Table_1.pdf : Table 1Description of Martin_Oehrli_Table_2.pdf : Table 2Description of Martin_Oehrli_Appendix_A.pdf : Appendix A: Deep Dive MethodologyDescription of Martin_Oehrli_Appendix_B.pdf : Appendix B: Sample workshop assessment surve