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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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research, data rescue efforts respond to the growing recognition of the value and reuse potential of data biding in unpublished records and collections of legacy research materials.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.
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.
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.
Digital Workflows at the National Agricultural Library and Implications for Preservation
(2018-02) Daniels, Morgan
This study was designed to surface needs for an organization-wide digital preservation infrastructure at the National Agricultural Library by examining the processes currently used at NAL in routine work with digital materials. It used an observation-based interview method to learn directly from staff members about their workflows with digital objects, combining the information gathered into models that depict their work. The report is organized to follow each of the four major digital workflows, ending with a discussion of the implications of the study for an overarching digital preservation program at the library.
Final Report and Recommendations of the Data Rescue Project at the National Agricultural Library
(2020-08) Clarke, Cooper T.; Shiue, Hilary Szu Yin
The National Agricultural Library (NAL) identified a need for a framework of guidance to support rapid appraisal and processing for scientific researchers’ collections after being offered collections of scientific data and data-rich materials that required immediate appraisal before acquisition. This Report and accompanying Data Rescue Processing Guide document the work and scholarship of the Data Rescue Project.
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.
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.