Browsing by Author "Coburn, Liza"

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    Assessing the Satisfaction and Engagement of DCN Curators
    (Data Curation Network, 2020-10-22) Coburn, Liza
    The Data Curation Network collectively curates research data deposited to academic and non-profit data repositories. Curators participating in the DCN, who bring a wide variety of subject and file type expertise, are matched with datasets from across the network of (currently 12) partner repositories. After the first year of piloting the DCN’s shared curation service we determined that a key consideration for a cross-institutional collaboration is the satisfaction of those participating. We launched a brief, anonymous survey in May 2020 to gauge the satisfaction of DCN curators, their engagement with the DCN community, and assess their interest in continuing their participation beyond the current grant phase (May 2018 - June 2021). We received 19 responses from the 24 DCN curators invited to take the survey (79% response rate). This summary report presents our findings and discusses the work done over the subsequent months to address curator feedback and better engage our community members in the DCN going forward.
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    Data Curation Services, Together!
    (2018-11-08) Johnston, Lisa; Blake, Mara; Carlson, Jake; Coburn, Liza; Herndon, Joel; Hull, Elizabeth; Hudson-Vitale, Cynthia; Imker, Heidi; Kozlowski, Wendy; Olendorf, Robert; McGeary, Timothy M; Stewart, Claire
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    Data Sharing Readiness in Academic Institutions
    (Data Curation Network, 2020-01-15) Johnston, Lisa R; Coburn, Liza
    In 2017, several members of the Data Curation Network authored the Academic Research Libraries (ARL) Data Curation Spec Kit, a survey asking 124 academic research institutions in the United States and Canada to self-assess their data repository and curation services (Hudson-Vitale et al., 2017a). Three years later, institutional support for data sharing is as relevant as ever. Next month, the Association of Public Land Grant Universities (APLU) and the Association of American Universities (AAU) will convene a national summit in Washington, DC to address how public universities may increase public access to their research, particularly in light of funder and journal requirements supporting data reuse and research transparency. So, we wondered, how has the academic landscape for data repository and curation services changed? To answer this question, we used website content analysis – a method that has been used successfully in recent years for examining the broader category of academic library research data services offerings (Yoon and Schultz, 2015; Kouper, Fear, Ishida, Kollen, & WIlliams, 2017) – to better understand data repository services in academic research libraries, building on the 2017 Spec Kit results.
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    Data supporting “Data Sharing Readiness in Academic Institutions” Version 1.0
    (2020-01-15) Johnston, Lisa R; Coburn, Liza; ljohnsto@umn.edu; Johnston, Lisa R; University Libraries
    To address how has the academic landscape for data repository and curation services changed we used website content analysis to better understand data repository services in academic research libraries, building on the 2017 ARL Spec Kit for Data Curation (Hudson-Vitale et al., 2017a). Of the 124 ARL institutions we chose to focus on academic institutions, and therefore excluded 10 civic libraries. For each of the remaining 114 ARL institutions we asked four research questions: Do they support data sharing via data repository services? How many datasets did they hold as of January 2020? What digital repository software platform was in use? How do our results compare with the 2017 ARL SPEC Kit data.
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    Presentation slides for Testing Our Assumptions: Preliminary Results from the DCN
    (2020-10-07) Coburn, Liza; Johnston, Lisa
    The data from year one of the DCN pilot have verified key assumptions about our collaborative approach to data curation, and these results have raised additional questions about capacity, equitable use of network resources, and sustained growth that we hope to answer by the end of this implementation phase.