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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Now showing 1 - 5 of 5
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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research, data rescue efforts respond to the growing recognition of the value and reuse potential of data biding in unpublished records and collections of legacy research materials.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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    Maintaining Institutional Historical Collections through Rapid Appraisal of Employee Files
    (2020-08) Shaw, Miranda; Nicholas, Phillip
    In the past decade, institutions like the National Agricultural Library (NAL) have not consistently preserved records documenting their history. This lack of documentation has the potential to damage the credibility and transparency of federal institutions like the NAL. This paper considers how employee’s personal work files can supplement other records to document the history of federal institutions, and suggests procedures for rapid, systematic appraisal of employees’ files to support efficient collection development. In an effort to fill gaps in the historical record of the NAL, Susan McCarthy, Associate Director for the NAL’s Knowledge Services Division, donated her collected analog and digital work papers—amassed over a thirty-year career—to NAL Special Collections. McCarthy also hired two archives fellows (the authors of this report) to assist Special Collections with processing her collected documents, and to conduct research on rapid appraisal methods to support efficient processing of this very large collection. We conducted an initial survey of McCarthy’s files and found valuable information pertaining to events and activities in the history of the NAL. In order to rapidly appraise those materials for the collection, we crafted a collection development policy specific for McCarthy’s documents by researching policies at other national libraries. The results uncovered in this process indicate that institutions should seriously consider supplementing historical collections with employee’s work files, and conducting outreach for external help when appraising donations for these collections.
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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.
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    National Agricultural Library: Digital Curation Plan
    (2016) Punzalan, Ricardo; Kriesberg, Adam; Daniels, Morgan; Gucer, Kathryn
    This report presents the observations, findings, and recommendations of the Agricultural Data Curation team at the University of Maryland’s College of Information Studies on digital curation and preservation at the National Agricultural Library (NAL). Through sustained engagement at the library involving the PI, postdoctoral fellows, and Masters fellows, we developed these recommendations for NAL to build an integrated and sustained digital preservation infrastructure which takes advantage of its position as one of the United States’ National Libraries and positions it to lead the USDA and agricultural community in providing next-generation information services.