Browsing by Subject "data management"
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Item Examining the Research Practices of Agricultural Scholars at the University of Minnesota - Twin Cities(2016) Farrell, Shannon L.; Kocher, MeganDuring the spring and summer of 2016, the University of Minnesota Libraries joined 18 other institutions to participate in Ithaka S+R’s Research Support Services Program to explore agricultural scholars’ research focus, research methods and publishing practices. This report summarizes our local findings, resulting from 16 interviews with University of Minnesota faculty from the College of Food, Agricultural and Natural Resources Sciences on the Twin Cities campus. It also offers suggestions for agriculture libraries and librarians based on the data we have gathered.Item First Year of "Creating a Data Management Plan": A New Workshop Offered by the University of Minnesota Libraries.(2012-04-25) Petsan, Beth; Lafferty, Meghan; Johnston, Lisa RThis poster was presented at the USAIN (United States Agricultural Information Network) 2012 Conference in Minneapolis-St. Paul, MN (April 29-May 2, 2012). The topic is a University of Minnesota Libraries' workshop called "Creating a Data Management Plan for your Grant Application."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.Item Partnerships in a Data Management Village: Exploring how research and library services can work together(2015) Hofelich Mohr, Alicia; Lindsay, Thomas; Johnston, Lisa RProviding data management services is a task that takes a village; a distributed model of support, involving collaboration among diverse institutional offices, is needed to do it well. Researchers especially benefit when specialized institutional support offices are aware of other relevant providers and the impact their services have on the management of data across the research life cycle. However, once a village is assembled, how do we work with members to be committed collaborators, rather than a passive referral network? In this presentation, we will describe a case study of our in-depth collaboration between the University Libraries and the College of Liberal Arts (CLA) at the University of Minnesota. Both groups are developing new suites of data management services to meet evolving researcher needs and rising demands for data management support. Working together has provided many advantages for sharing resources and knowledge, but also has presented challenges, including how to define the respective roles of college-level and university-wide data management services, and how formalized collaborations may work. We will describe these challenges and how the collective and complementary skills of our offices will provide researchers with support across much larger portions of the research life cycle than either office could provide alone.Item QuARCC: The Quality Assurance Research Reproducibility Collaborative(2017) Hegstad-Davies, Rebecca L; Sayre, Franklin D; Laube, Katrina; Bakker, Caitlin; Shimizu, YItem Understanding Researcher Needs in Data Management: A Comparison of Four Colleges in a Large American University(2015) Hofelich Mohr, Alicia; Braun, Steven; Bishoff, Carolyn; Bishoff, Josh; Johnston, Lisa RThe diverse nature of research makes identifying needs and providing support for data management a complex task in an academic setting. To better understand this diversity, we compare the findings from three surveys on research data management delivered to faculty across 104 departments in the University of Minnesota - Twin Cities campus. Each survey was separately run in the Medical School, the College of Liberal Arts, the College of Food, Agricultural, and Natural Resource Sciences and the College of Science & Engineering and modified to use language that paralleled the different cultural understandings of research and data across these disciplines. Our findings reveal common points of need, such as a desire for more data management support across the research life cycle, with the strongest needs related to preparing data for sharing, data preservation, and data dissemination. However, the results also reveal striking differences across the disciplines in attitudes and perceptions toward data management, awareness of existing requirements, and community expectations. These survey results can be used by others to demonstrate that a one-size-fits-all approach to supporting data management is not appropriate for a large research university and that the services developed should be sensitive to discipline-specific research practices and perceived needs.