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.Shiue, Hilary Szu YinSubject: search.filters.subject.digital curation

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    Data Rescue at the U.S. National Agricultural Library: Case Studies of 3 Hybrid Collections
    (Research Data Alliance 16th Plenary, 2020-11-09) Shiue, Hilary Szu Yin; Clarke, Cooper; Fenlon, Katrina
    While the open science movement facilitates discussions in managing, preserving and curating data from active and ongoing research, data rescue efforts respond to the growing recognition of the value and reuse potential of data biding in unpublished records and collections of legacy research materials. Making data embedded in these records available for reuse may support longitudinal analysis, meta-analysis, and cross-disciplinary research. The data rescue project was led by graduate fellows in the University of Maryland College of Information Studies (iSchool) Digital Curation Fellowship, a cooperative agreement between iSchool and the U.S. National Agricultural Library. We identified 18 assessment factors after conducting three case studies to investigate potential issues of curating collections with the purpose of data recovery and reuse. Although there is no one-size-fit-all solution to process and appraise data-rich collections, the 18 assessment factors assist curators to navigate different issues and find most suitable methods to make research data available.
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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.
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    Data Rescue Processing Guide: A Practical Guide to Processing Preservation-Ready Data from Research Data Collections
    (2020-09-29) Clarke, Cooper T.; Shiue, Hilary Szu Yin; Shiue, Hilary Szu Yin; Fenlon, Katrina
    This processing guide was developed for use in combination with rapid data appraisal methodology in order to make valuable data available to users as quickly as possible. Data rescue is the process of identifying, intervening, and revitalizing data-rich materials at risk of loss to produce preservation-ready data. Data-rich materials are any medium, either digital and/or analog, that contain data and/or research findings. Preservation-ready data are the final product of processing, stabilized and with sufficient description for preservation and dissemination. Rapid appraisal differs from traditional appraisal in that it applies a uniform framework to determine the information’s values as quickly as possible, enabling data rescue. This processing guide was written by University of Maryland (UMD) graduate students in the College of Information Studies for use by the National Agricultural Library (NAL) of the U.S. Department of Agriculture (USDA), through the NAL-UMD Digital Curation Fellows program.