Carolyn Bishoff

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Now showing 1 - 7 of 7
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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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    Virtual Makerspace Workshops: Practical Lessons for Adapting Content and Technology
    (International Symposium on Academic Makerspaces, 2021-11-21) Bishoff, Carolyn; Carlson, Tiffany; Jubara, Rami; Heinz, Charlie
    The University of Minnesota Libraries manages two makerspaces that are designed to support creative work, experiential learning, and student wellbeing across majors and disciplines. The library makerspaces are not formally integrated with college or departmental curricula, so anyone using the space is doing so completely voluntarily. Because of this, our staff engage in a significant amount of awareness-building and outreach to students, faculty, and staff. Workshops are one of the primary ways we invite users into the library makerspaces. These events – Design for 3D Printing, Podcasting 101, and Bullet Journaling, to name a few – provide a low-barrier way to visit the space, learn a skill, and meet some of our staff. Students come to the university with a variety of perceptions of makerspaces and may have assumptions or associations that originated in primary school. Workshops give us a chance to establish relationships, challenge assumptions about makerspaces, and provide positive experiences for first-time users. When classes and operations went remote in March 2020, our workshops did too. Our staff adapted our lesson plans, learned new technologies, expanded our online presence, and taught hands-on activities in a virtual environment.
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    Outreach, Collaboration, Collegiality: Evolving Approaches to Library Video Game Services
    (2015) Bishoff, Carolyn; Farrell, Shannon L.; Neeser, Amy E.
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    Data Management Needs Assessment - Surveys in CLA, AHC, CSE, and CFANS
    (2015) Hofelich Mohr, Alicia; Bishoff, Josh; Johnston, Lisa R; Braun, Steven; Storino, Christine; Bishoff, Carolyn
    Researcher's data management needs were assessed at four colleges with in the University of Minnesota: The College of Liberal Arts (CLA), the Academic Health Center (AHC), the College of Science and Engineering (CSE), and the College of Food, Agriculture, and Natural Resource Sciences (CFANS). The initial survey was designed in CLA and featured a branched design that presented researchers one of two versions of the questions based on how respondents described the products of their scholarship - as "data" or "research materials". The survey was then customized for the other colleges, adding or editing questions based on feedback from disciplinary experts, while maintaining comparability across surveys. Surveys were run between September 2013 and and February 2015.
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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.
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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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    Analyzed Data Management Plans (DMPs) from Successful University of Minnesota Grants from the National Science Foundation, 2011-2014
    (2015-03-31) Johnston, Lisa R; Bishoff, Carolyn; McGrory, John; Storino, Chris; Swendsrud, Anders; ljohnsto@umn.edu; Johnston, Lisa R
    Federal funding agencies are asking principal investigators (PIs) to specify their plans for describing, storing, securing, sharing, and preserving their research data in Data Management Plans (DMPs) included with their grant proposal. This change in sponsored research is best exemplified by the National Science Foundation (NSF) which in 2010 announced that all grants submitted after January 18th, 2011 must include a one- to two-page DMP with all new proposals. In order to review the plans for how University of Minnesota researchers plan to manage, store, describe, protect, and share and preserve their data, a review instrument was created and implemented by the University Libraries in the summer of 2014. Our local study of DMPs in successful NSF grant applications from January 2011 - June 2014 was opt-in by U of M PIs and the libraries collected 182 data management plans for our study, accounting for 41% of the total number of plans solicited. The deidentified data used in our analysis and our survey instrument are presented here.