Carolyn Bishoff

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https://hdl.handle.net/11299/174932

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Browsing Carolyn Bishoff by Type "Presentation"

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    Follow the money: Getting chemists to share their data
    (Research Data Access & Preservation Summit, 2018-03-22) Lafferty, Meghan; Bishoff, Carolyn; Farrell, Shannon
    The 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.
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    A Review of Data Management Plans (DMPs) from Successful National Science Foundation Grants from the University of Minnesota Twin Cities, 2011-2014
    (2015-02-27) Johnston, Lisa R; Bishoff, Carolyn
    In order to better understand the ongoing needs of campus researchers for managing and sharing their research data the University Libraries conducted a local study of Data Management Plans (DMPs) included in successful National Science Foundation grant applications from January 2011 - June 2014. Participation in the study was opt-in by U of M principal investigators (PIs) on the grants. Thanks to support within the colleges for participation the libraries collected 182 data management plans for our study, accounting for 41% of the total number of plans solicited. Overall, the College of Science of Engineering accounted for the majority of plans, accounting for 80% of the plans included in the review. The results of this study will inform the development of robust and targeted data services, both from the libraries and our campus partners, that aim to increase the impact of research produced at the University of Minnesota.
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    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 R
    The 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.