Browsing by Subject "embedded librarianship"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Extending Our Reach: Embedding Library Resources and Services within Extension(ACRL, 2011) Mastel, KristenThis chapter will discuss how the University of Minnesota is seeking to reach out to previously underserved Extension staff through virtual and personal services. A variety of techniques have been used, such as trend spotting, lurking and active engagement, to identify the strengths and weakness in our library programming and services for Extension staff; with this information we are able to develop strategies for outreach opportunities.Item Follow the money: Getting chemists to share their data(Research Data Access & Preservation Summit, 2018-03-22) Lafferty, Meghan; Bishoff, Carolyn; Farrell, ShannonThe University of Minnesota Libraries was invited to partner with an interdisciplinary research center to strengthen their data management practices & pilot a data project at the request of NSF. Data sharing is not the norm for chemistry & materials science researchers but we had the support of advocates in the center and made practical compromises that encouraged buy-in and participation, led to well-described and decently organized data, and a workflow that we adapted to their time constraints and publishing cycle. We faced familiar obstacles to fully FAIR data: friction with researchers, complex and heterogeneous data sets, and limitations of our repository systems. Our university has an established data curation process but each data submission was highly interdisciplinary and it was the first time most of us had encountered the data formats we curated. Additional pressure came from the NSF which expected the Center to be a leader in data management. The project is a scaled effort to change the data sharing culture of a large research center using a collaboration of embedded liaison librarians and data curators. We had no budget for this project and relied on existing infrastructure and staff. This presentation will examine several decisions and compromises that frame the tension between the FAIR ideal and the limitations we had on people, systems, and data.