Category: Digital Curation & Digital Preservation

"National Archives Releases Digital Preservation Framework for Public Comment"

The National Archives has released "National Archives Releases Digital Preservation Framework for Public Comment."

Here's an excerpt:

The National Archives and Records Administration is seeking public comment and discussion on our digital preservation framework, which consists of our approach to determining risks faced by electronic files, and our plans for preserving different types of file formats. The public is encouraged to join the discussion, September 16 through November 1, 2019, on GitHub. . . .

This is evidenced by the June 2019 direction (M-19-21, Transition to Electronic Records) to Federal agencies to transition business processes and record keeping to a fully electronic environment and to end the National Archives’ acceptance of paper records by December 31, 2022.

The National Archives' digital preservation subject matter experts, led by Director of Digital Preservation Leslie Johnston, have been hard at work to prepare the National Archives for this change. They have formalized a set of documents that describe how we identify risks to digital files and prioritize them for action, and created specific plans for the preservation of these many file formats.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Progress in Research Data Services: An International Survey of University Libraries"

Andrew M Cox et al. have published "Progress in Research Data Services: An International Survey of University Libraries" in the International Journal of Digital Curation.

Here's an excerpt:

University libraries have played an important role in constructing an infrastructure of support for Research Data Management at an institutional level. This paper presents a comparative analysis of two international surveys of libraries about their involvement in Research Data Services conducted in 2014 and 2018. The aim was to explore how services had developed over this time period, and to explore the drivers and barriers to change. In particular, there was an interest in how far the FAIR data principles had been adopted.

Services in nearly every area were more developed in 2018 than before, but technical services remained less developed than advisory. Progress on institutional policy was also evident. However, priorities did not seem to have shifted significantly. Open ended answers suggested that funder policy, rather than researcher demand, remained the main driver of service development and that resources and skills gaps remained issues. While widely understood as an important reference point and standard, because of their relatively recent publication date, FAIR principles had not been widely adopted explicitly in policy.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Updating the Data Curation Continuum: Not Just Data, Still Focussed on Curation, More Domain-Oriented"

Andrew Treloar and Jens Klump have published "Updating the Data Curation Continuum: Not Just Data, Still Focussed on Curation, More Domain-Oriented" in the International Journal of Digital Curation.

Here's an excerpt:

The Data Curation Continuum was developed as a way of thinking about data repository infrastructure. Since its original development over a decade ago, a number of things have changed in the data infrastructure domain. This paper revisits the thinking behind the original data curation continuum and updates it to respond to changes in research objects, storage models, and the repository landscape in general.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Research Data Management and the Evolutions of Scholarship: Policy, Infrastructure and Data Literacy at KU Leuven"

Tom Willaert et al. have published "Research Data Management and the Evolutions of Scholarship: Policy, Infrastructure and Data Literacy at KU Leuven" in LIBER Quarterly.

Here's an excerpt:

This case study critically examines ongoing developments in contemporary scholarship through the lens of research data management support at KU Leuven, and KU Leuven Libraries in particular. By means of case-based examples, current initiatives for fostering sound scientific work and scholarship are considered in three associated domains: support for policy-making, the development of research infrastructures, and digital literacy training for students, scientists and scholars. It is outlined how KU Leuven Libraries collaborates with partner services in order to contribute to KU Leuven's research data management support network. Particular attention is devoted to the innovations that facilitate such collaborations. These accounts of initial experiences form the basis for a reflection on best practices and pitfalls, and foreground a number of pertinent challenges facing the domain of research data management, including matters of scalability, technology acceptance and adoption, and methods for effectively gauging and communicating the manifold transformations of science and scholarship.

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Digital Art through the Looking Glass: New Strategies for Archiving, Collecting and Preserving in Digital Humanities

Edition Donau-Universität has released Digital Art through the Looking Glass: New Strategies for Archiving, Collecting and Preserving in Digital Humanities.

Here's an excerpt:

The aim of this collection is to focus on how we need to redefine preservation methods for digital art by creating a transdisciplinary dialogue between all the involved stakeholders and how we can archive digital artworks by acknowledging their authenticity and mediality. The discussion goes beyond preservation as such and questions how digital artworks can be further re-used for curatorial and dissemination projects, and as research data.

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"Lost or Found? Discovering Data Needed for Research"

have self-archived "Lost or Found? Discovering Data Needed for Research."

Here's an excerpt:

Finding or discovering data is a necessary precursor to being able to reuse data, although relatively little large-scale empirical evidence exists about how researchers discover, make sense of and (re)use data for research. This study presents evidence from the largest known survey investigating how researchers discover and use data that they do not create themselves. We examine the data needs and discovery strategies of respondents, propose a typology for data (re)use and probe the role of social interactions and other research practices in data discovery, with the aim of informing the design of community-centric solutions and policies.

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"Practical Application of a Data Stewardship Maturity Matrix for the NOAA OneStop Project"

Ge Peng et al. have published "Practical Application of a Data Stewardship Maturity Matrix for the NOAA OneStop Project" in the Data Science Journal.

Here's an excerpt:

Assessing the stewardship maturity of individual datasets is an essential part of ensuring and improving the way datasets are documented, preserved, and disseminated to users. It is a critical step towards meeting U.S. federal regulations, organizational requirements, and user needs. However, it is challenging to do so consistently and quantifiably. The Data Stewardship Maturity Matrix (DSMM), developed jointly by NOAA's National Centers for Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites–North Carolina (CICS-NC), provides a uniform framework for consistently rating stewardship maturity of individual datasets in nine key components: preservability, accessibility, usability, production sustainability, data quality assurance, data quality control/monitoring, data quality assessment, transparency/traceability, and data integrity. So far, the DSMM has been applied to over 800 individual datasets that are archived and/or managed by NCEI, in support of the NOAA's OneStop Data Discovery and Access Framework Project. As a part of the OneStop-ready process, tools, implementation guidance, workflows, and best practices are developed to assist the application of the DSMM and described in this paper. The DSMM ratings are also consistently captured in the ISO standard-based dataset-level quality metadata and citable quality descriptive information documents, which serve as interoperable quality information to both machine and human end-users. These DSMM implementation and integration workflows and best practices could be adopted by other data management and stewardship projects or adapted for applications of other maturity assessment models.

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"Skills, Standards, and Sapp Nelson’s Matrix: Evaluating Research Data Management Workshop Offerings"

Philip Espinola Coombs et al. have published "Skills, Standards, and Sapp Nelson's Matrix: Evaluating Research Data Management Workshop Offerings" in the Journal of eScience Librarianship.

Here's an excerpt:

Here's an excerpt from the announcement:

Objective: To evaluate library workshops on their coverage of data management topics.

Methods: We used a modified version of Sapp Nelson’s Competency Matrix for Data Management Skills, a matrix of learning goals organized by data management competency and complexity level, against which we compared our educational materials: slide decks and worksheets. We examined each of the educational materials against the 333 learning objectives in our modified version of the Matrix to determine which of the learning objectives applied.

Conclusions: We found it necessary to change certain elements of the Matrix’s structure to increase its clarity and functionality: reinterpreting the behaviors, shifting the organization from the three domains of Bloom’s taxonomy to increasing complexity solely within the cognitive domain, as well as creating a comprehensive identifier schema. We appreciated the Matrix for its specificity of learning objectives, its organizational structure, the comprehensive range of competencies included, and its ease of use. On the whole, the Matrix is a useful instrument for the assessment of data management programming.

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"Building A National Research Data Management Course for Health Information Professionals"

Jessica Van Der Volgen and Shirley Zhao have published "Building A National Research Data Management Course for Health Information Professionals" in the Journal of eScience Librarianship.

Here's an excerpt:

Background: In August 2017 the National Network of Libraries of Medicine Training Office (NTO) was awarded an administrative supplement from the National Library of Medicine (NLM) to create training for librarians in biomedical and health research data management (RDM). The primary goal of the training was to enable information professionals to initiate or enhance RDM at their institutions.

Case Presentation: An eight-week online course was developed to address key concepts in RDM. Each module was organized around measurable learning objectives using existing subject resources, such as readings, tutorials, and videos. Within each module, an expert in the field co-facilitated relevant discussions, created and graded a practical assignment, and answered questions. Thirty-eight participants were selected for this initial cohort. Mentors were assigned to each participant for guidance in completing a required project action plan to further their RDM goals at their institution. The course was evaluated through pre- and post-tests and an online questionnaire.

Results: Thirty participants successfully completed the online course work and project, and gathered at the National Institutes of Health for a Capstone Summit. Students demonstrated improved knowledge of RDM concepts between the pre- and post-tests. Most students also self-reported increased skill and confidence. Practical assignments with individual feedback from experienced data librarians were the most valued aspect of the course. Time to complete each module was underestimated.

Conclusions: The initial offering of this training program improved the RDM skills and knowledge of participants and enabled students to add or enhance services at their institutions. Further investigations are necessary to determine the longer-term impact on the individuals and their libraries. While many of the participants will need additional training to become part of the data-ready workforce of health information professionals, completing this training is an important step in their professional development.

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"Digitization and the Future of Natural History Collections"

Brandon Hedrick et al. have self-archived "Digitization and the Future of Natural History Collections."

Here's an excerpt:

Natural history collections (NHCs) are the foundation of historical baselines for assessing anthropogenic impacts on biodiversity. Along these lines, the online mobilization of specimens via digitization–the conversion of specimen data into accessible digital content–has greatly expanded the use of NHC collections across a diversity of disciplines. We broaden the current vision of digitization (Digitization 1.0)–whereby specimens are digitized within NHCs–to include new approaches that rely on digitized products rather than the physical specimen (Digitization 2.0). Digitization 2.0 builds upon the data, workflows, and infrastructure produced by Digitization 1.0 to create digital-only workflows that facilitate digitization, curation, and data linkages, thus returning value to physical specimens by creating new layers of annotation, empowering a global community, and developing automated approaches to advance biodiversity discovery and conservation. These efforts will transform large-scale biodiversity assessments to address fundamental questions including those pertaining to critical modern issues of global change.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"The MASi Repository Service—Comprehensive, Metadata-Driven and Multi-Community Research Data Management"

Richard Grunzke et al. have published "The MASi Repository Service—Comprehensive, Metadata-Driven and Multi-Community Research Data Management" in Future Generation Computer Systems.

Here's an excerpt:

Here, we present the architecture and developments of the Metadata Management for Applied Sciences (MASi) project that is currently building a comprehensive research data management service. MASi extends the existing KIT Data Manager framework by a generic metadata programming interface and a generic graphical web interface. Furthermore, MASi is OAI compliant and supports the OAI-PMH protocol while providing support for provenance information using ProvONE, a well-established and accepted provenance model. To illustrate the practical applicability of the MASi service, we present the adoption of initial use cases within geography, chemistry and digital humanities.

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"Building Open Access to Research (OAR) Data Infrastructure at NIST"

Gretchen Greene, Raymond Plante, and Robert Hanisch have published "Building Open Access to Research (OAR) Data Infrastructure at NIST" in Data Science Journal.

Here's an excerpt:

As a National Metrology Institute (NMI), the USA National Institute of Standards and Technology (NIST) scientists, engineers and technology experts conduct research across a full spectrum of physical science domains. NIST is a non-regulatory agency within the U.S. Department of Commerce with a mission to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life. NIST research results in the production and distribution of standard reference materials, calibration services, and datasets. These are generated from a wide range of complex laboratory instrumentation, expert analyses, and calibration processes. In response to a government open data policy, and in collaboration with the broader research community, NIST has developed a federated Open Access to Research (OAR) scientific data infrastructure aligned with FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Through the OAR initiatives, NIST's Material Measurement Laboratory Office of Data and Informatics (ODI) recently released a new scientific data discovery portal and public data repository. These science-oriented applications provide dissemination and public access for data from across the broad spectrum of NIST research disciplines, including chemistry, biology, materials science (such as crystallography, nanomaterials, etc.), physics, disaster resilience, cyberinfrastructure, communications, forensics, and others. NIST’s public data consist of carefully curated Standard Reference Data, legacy high valued data, and new research data publications. The repository is thus evolving both in content and features as the nature of research progresses. Implementation of the OAR infrastructure is key to NIST’s role in sharing high integrity reproducible research for measurement science in a rapidly changing world.

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"The Lives and After Lives of Data"

Christine L. Borgman has published "The Lives and After Lives of Data" in the Harvard Data Science Review.

Here's an excerpt:

The most elusive term in data science is 'data.' While often treated as objects to be computed upon, data is a theory-laden concept with a long history. Data exist within knowledge infrastructures that govern how they are created, managed, and interpreted. By comparing models of data life cycles, implicit assumptions about data become apparent. In linear models, data pass through stages from beginning to end of life, which suggest that data can be recreated as needed. Cyclical models, in which data flow in a virtuous circle of uses and reuses, are better suited for irreplaceable observational data that may retain value indefinitely. In astronomy, for example, observations from one generation of telescopes may become calibration and modeling data for the next generation, whether digital sky surveys or glass plates. The value and reusability of data can be enhanced through investments in knowledge infrastructures, especially digital curation and preservation. Determining what data to keep, why, how, and for how long, is the challenge of our day.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

Research Data Curation Bibliography, Version 10 PDF Released

Digital Scholarship has released a PDF of the Research Data Curation Bibliography, Version 10.

Created from the HTML file, this unpaginated PDF with basic formatting makes it easier to print the lengthy bibliography.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Digital Curation at Work: Modeling Workflows for Digital Archival Materials"

Colin Post et al. have self-archived "Digital Curation at Work: Modeling Workflows for Digital Archival Materials."

Here's an excerpt:

This paper describes and compares digital curation workflows from 12 cultural heritage institutions that vary in size, nature of digital collections, available resources, and level of development of digital curation activities.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

Share–Publish–Store–Preserve. Methodologies, Tools and Challenges for 3D Use in Social Sciences and Humanities

Anas Alaoui M'Darhri et al. have self-archived "Share–Publish–Store–Preserve. Methodologies, Tools and Challenges for 3D Use in Social Sciences and Humanities."

Here's an excerpt:

Through this White Paper, which gathers contributions from experts of 3D data as well as professionals concerned with the interoperability and sustainability of 3D research data, the PARTHENOS project aims at highlighting some of the current issues they have to face, with possible specific points according to the discipline, and potential practices and methodologies to deal with these issues. During the workshop, several tools to deal with these issues have been introduced and confronted with the participants experiences, this White Paper now intends to go further by also integrating participants feedbacks and suggestions of potential improvements. Therefore, even if the focus is put on specific tools, the main goal is to contribute to the development of standardized good practices related to the sharing, publication, storage and long-term preservation of 3D data.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap