Digital Curation Fellows - National Agricultural Library

Permanent URI for this collectionhttp://hdl.handle.net/1903/26345

The iSchool Digital Curation Fellows program is a collaboration with the National Agricultural Library (NAL) to match students across iSchool programs with digital curation research opportunities at NAL. In collaboration with iSchool faculty and postdoctoral associates, students work with divisions across the NAL to solve problems and conduct research on various NAL digital curation initiatives, including data recovery and data curation, digital preservation, archiving and digitization, data science and analytics, user experience, and building historical digital collections for public use. This collection represents the outcomes of the NAL iSchool Digital Curation Fellows program.

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Author: search.filters.author.Clarke, Cooper T.Subject: search.filters.subject.data reuse

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    Recovering and Reusing Archival Data for Science: Investigating Curatorial Practices Across Disciplines
    (Research Data Alliance, 2021-11-03) Shiue, Hilary Szu Yin; Sorensen, Amanda; Clarke, Cooper T.; Fenlon, Katrina
    Extensive, scattered collections of historical research records and legacy scientific data have largely untapped, but potentially enormous value to ongoing and future research. While research and practice in data reuse and curation have focused almost exclusively on contemporary scientific data—data from active or recent research, data already hosted in repositories, and data which are already computationally or analytically amenable—scattered data rescue initiatives, or efforts to recover and reuse historical data, have illuminated the potential benefits of curating historical data for current and future reuse in a variety of contexts. Yet we know little about the range and impact of existing efforts to recover historical data across disciplines, the unique curation challenges of historical scientific materials, and the recovery and reuse practices of scientists and curators specifically directed at archival or defunct data. The "Recovering and Reusing Archival Data for Science" project (RRAD-S) is conducting semi-structured interviews with scientists and curators to investigate recovery and reuse efforts directed at archival data, including data in the historical and special collections of libraries and archives, but also data lurking in boxes of unpublished documents in the basements of research centers. Through interviews with experienced domain experts across various disciplines and organizations, we are investigating the landscape of current data recovery efforts and identifying differences and commonalities among the priorities, processes, and practices of data recovery and reuse in different research contexts. In particular, we are examining differences in the practices of professional data curators and scientists or domain experts. The RRAD-S study builds on prior case study research, which developed assessment factors and a processing guide to assist memory institutions in evaluating the challenges and opportunities of recovering data from archival collections. The current phase of research will translate findings into practical guidance for the scientific and curatorial communities, characterize historical data reuse in novel contexts, and illuminate the curatorial practices of scientists themselves in the course of reuse.
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    Data rescue: An assessment framework for legacy research collections
    (2020-09-30) Hoffman, Kelly M.; Clarke, Cooper T.; Shiue, Hilary Szu Yin; Nicholas, Phillip; Shaw, Miranda; Fenlon, Katrina
    Widespread investments in the reproducibility and reuse of scientific data have spurred an increasing recognition of the potential value of data biding in unpublished records and collections of legacy research materials, such as scientists’ papers, historical publications, and working files. Recovering usable scientific data from legacy collections constitutes one kind of data rescue: the application of selected data curation processes to data at imminent risk of loss. Given the growing interest in data-intensive science and growing movement toward computationally amenable collections in memory institutions, the National Agricultural Library and other curation institutions need systematic approaches to processing legacy collections with the specific goal of retrieving reusable or historically valuable scientific data. This white paper reports on research conducted under the auspices of the Digital Curation Fellows Program, a collaborative research initiative of the United States Department of Agriculture’s National Agricultural Library and the University of Maryland College of Information Studies. We offer a framework for assessing collections of scientific records for the purpose of data rescue, developed through research on three case studies of agricultural research collections. This framework aims to guide data rescue initiatives at the National Agricultural Library and other agricultural research centers, and to provide conceptual and practical framing for emerging conversations around data rescue in the agricultural research community and across disciplines.