Lisa R Johnston

Persistent link for this collectionhttps://hdl.handle.net/11299/92081

As Data Management & Curation Lead and co-director of the University Digital Conservancy I coordinate the library's efforts around digital scholarship and research data management, access, and archiving. Prior to this I served as library liaison to the Physics, Astronomy, and Geology departments (2007-2011). My research areas of focus are scientific data curation, citation analysis, information-seeking behavior and web development of user-centered tools to access information.

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Browsing Lisa R Johnston by Type "Report"

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    Definitions of Data Curation Activities used by the Data Curation Network
    (2016-10) Johnston, Lisa R; Carlson, Jake; Hudson-Vitale, Cynthia; Imker, Heidi; Kozlowski, Wendy; Olendorf, Robert; Stewart, Claire
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    Implementing Research Cyberinfrastructure for the 21st Century
    (University of Minnesota, 2009) Anderson, Tracy; Gjerdinge, Craig; Herrman, Bryan; Himes, Katherine; Johnston, Lisa R
    As a result of innovative partnerships between the Office of Information Technology, collegiate units, and other Central units, outstanding technological support systems for administrative and academic needs have been developed to serve faculty, staff and students. Central and local IT support staffs maintain servers and desktop computers to ensure availability and security of information technology tools and resources. The University’s Digital Media Center, along with academic technology support staffs in local units, provides a variety of services to instructors and students using technology in teaching and learning. . Dramatic advances in information technology make way for exciting new opportunities for research as well. New technologies allow projects to span disciplines and institutions, enabling researchers to seek new answers to critical questions in ways that were impossible just years or even months ago. Indeed, research computing is a top priority for leading universities and research institutions around the globe; furthermore, cyberinfrastructure is seen as a key factor in securing research funding and attracting and retaining top faculty and students. The expanded research agendas in many disciplines are now outpacing the computing resources available to individual researchers, departments, or even institutions. Enabling this research requires large-scale investments in high-performance computing, storage and networking, as well as the development of cyberinfrastructure to integrate these components into a meaningful whole. Cyberinfrastructure includes the instruments, sensors, high performance computational systems, massive storage systems, data resources, and visualization facilities, tied together by high speed networks and made to work together by advanced software to accomplish goals that would not be possible by any single information technology system. It also includes the people, processes, training, security, policies, and capabilities to sustain the systems and networks over time. Implementing cyberinfrastructure requires a high level of coordination and collaboration between researchers and an information technology workforce with expertise in scientific computing.
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    Ratings of Importance for Data Curation Activities
    (2016-12-15) Johnston, Lisa R; Carlson, Jake; Hudson-Vitale, Cynthia; Imker, Heidi; Kozlowski, Wendy; Olendorf, Robert; Stewart, Claire
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    Results of the Fall 2016 Data Curation Pilot
    (2017-03-15) Johnston, Lisa R; Carlson, Jake; Hudson-Vitale, Cynthia; Imker, Heidi; Kozlowski, Wendy; Olendorf, Robert; Stewart, Claire
    The Data Curation Network began the planning phase of our project with a one-year grant from the Alfred P. Sloan foundation in May 2016. The project will develop a shared staffing model for curating research data that draws from the expertise across multiple institutions in order to broaden the depth and breadth of curation services beyond what a single institution might offer alone. In the fall of 2016, we conducted two rounds of pilots involving data curation workflows. Our primary goals were to 1) identify what our (actual) individual curation practices were in order to compare curation steps taken, 2) begin to establish what training network curators would need, and 3) identify any issues, misaligned expectations, and/or conflicts with the goals of the project.
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    Results of the Fall 2016 Researcher Engagement Sessions
    (2017-03-09) Johnston, Lisa R; Carlson, Jake; Hudson-Vitale, Cynthia; Imker, Heidi; Kozlowski, Wendy; Olendorf, Robert; Stewart, Claire
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    Results of the Librarian-Focused Rankings of the Data Curation Activities
    (2017-05-19) Johnston, Lisa R; Carlson, Jake; Hudson-Vitale, Cynthia; Imker, Heidi; Kozlowski, Wendy; Olendorf, Robert; Stewart, Claire
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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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    The Supporting Documentation for Implementing the Data Repository for the University of Minnesota (DRUM): A Business Model, Functional Requirements, and Metadata Schema
    (2015-04) University of Minnesota Libraries
    The University Libraries launched the Data Repository for the University of Minnesota (DRUM) in November 2014. This service was developed and implemented by a group in the libraries called the Data Management and Curation Initiative (DMCI) with sponsorship by John Butler (Associate University Librarian for Data & Technology). The project team included Lisa Johnston (Project Lead), Jon Nichols (Technology Lead), Josh Bishoff, Steven Braun, Carol Kussmann, Francine Dupont Crocker, Kevin Dyke, Stephen Hearn, Alicia Hofelich-Mohr, Eric Larson, Erik Moore, Arvid Nelsen, Carolyn Rauber, Justin Schell, Bill Tantzen, and Amy West. The work products of the group presented here include the DMCI Business and Service Model that defines the draft policies, rational for data management and curation services, a proposed staffing model for distributed data curation, and initial first year budget. Other supporting documents for the launch of the repository include the Service and Functional Requirements that led the development of DRUM in the DSpace software (V 4.2) and the metadata schema, based on dublin core, for the data repository submission form and public access record.
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    A Workflow Model for Curating Research Data in the University of Minnesota Libraries: Report from the 2013 Data Curation Pilot
    (University Digital of Minnesota Conservancy, 2014-01-19) Johnston, Lisa R
    The 2013 Data Curation Project set out to test and expand the University Libraries’ programmatic and technical capacities to support research data management needs on campus by establishing a fixed-term data curation pilot. This pilot utilized our current suite of services and expertise in the University with the objective of developing a model workflow for curating a variety of types of research data in the Libraries. Specifically, in eight months, this project resulted in 1) a data curation workflow utilizing existing university resources; 2) five pilot research datasets that were solicited, selected, and curated for discovery and reuse in the libraries’ digital repository, the University Digital Conservancy, at the persistent URL, http://purl.umn.edu/160292; and 3) and a summary report describing the successes and shortcomings of this approach. This report summarizes the steps taken to curate the datasets in the pilot, faculty needs and reactions to the result, and in addition to the specific dataset treatments, an overall data curation workflow is presented that outlines the steps needed for any dataset. A discussion of this process provides some useful lessons learned. As a result of this project, the University Libraries now hold a more realistic sense of the overall capacities and expertise needed to develop a sustainable data curation service model. Additionally, the Libraries are better prepared to fine-tune and implement selected recommendations from previous assessments and committee reports.