https://dx.doi.org/10.5195%2Fjmla.2017.47

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.

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

https://library.ucsd.edu/news-events/uc-san-diego-library-and-texas-digital-library-collaborate-to-transform-digital-preservation-possibilities-for-sensitive-data/

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.

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

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

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

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

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

Sawood Alam et al. have self-archived "Supporting Web Archiving via Web Packaging."

Here's an excerpt:

We describe challenges related to web archiving, replaying archived web resources, and verifying their authenticity. We show that Web Packaging has significant potential to help address these challenges and identify areas in which changes are needed in order to fully realize that potential.

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

https://doi.org/10.1002/asi.24244

Daniel S. Katz et al. have self-archived "Software Citation Implementation Challenges."

Here's an excerpt:

The main output of the FORCE11 Software Citation working group (this https URL) was a paper on software citation principles (this https URL) published in September 2016. This paper laid out a set of six high-level principles for software citation (importance, credit and attribution, unique identification, persistence, accessibility, and specificity) and discussed how they could be used to implement software citation in the scholarly community. In a series of talks and other activities, we have promoted software citation using these increasingly accepted principles. At the time the initial paper was published, we also provided guidance and examples on how to make software citable, though we now realize there are unresolved problems with that guidance. The purpose of this document is to provide an explanation of current issues impacting scholarly attribution of research software, organize updated implementation guidance, and identify where best practices and solutions are still needed.

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

Kirsty Merrett et al. have published "The Administrative Load of Sharing Sensitive Data—Challenges and Solutions?" in the International Journal of Digital Curation.

Here's an excerpt:

Sharing data openly has become a straightforward process at the University of Bristol. The University's top funders mandate or recommend data sharing as a condition of funding, and many publishers require access to research data to enable results of published articles to be verified. The University has provided a dedicated data repository to support this since 2015, and demand for open publication has risen steadily since its inception. However, an increasing number of requests for sharing data relate to data that has ethical, legal or commercial sensitivities and so cannot be published openly.

Rather than discuss the wide-ranging ethical implications of data sharing, this practice paper will focus on the secure sharing of sensitive data that has ethical approval and, where required, has the necessary consent in place, from the perspective of an institution that has already decided to undertake the work inherent in sharing sensitive data. The specific purpose is to detail the workflow and administrative tasks integral in this and to highlight the types of challenges encountered.

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

Maria J. Cruz et al. have published "From Passive to Active, From Generic to Focussed: How Can an Institutional Data Archive Remain Relevant in a Rapidly Evolving Landscape? " in the International Journal of Digital Curation.

Here's an excerpt:

Founded in 2008 as an initiative of the libraries of three of the four technical universities in the Netherlands, the 4TU.Centre for Research Data (4TU.Research Data) has provided a fully operational, cross-institutional, long-term archive since 2010, storing data from all subjects in applied sciences and engineering. Presently, over 90% of the data in the archive is geoscientific data coded in netCDF (Network Common Data Form)—a data format and data model that, although generic, is mostly used in climate, ocean and atmospheric sciences. In this practice paper, we explore the question of how 4TU.Research Data can stay relevant and forward-looking in a rapidly evolving research data management landscape. In particular, we describe the motivation behind this question and how we propose to address it.

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

http://elegaldeposit.org/documents/18208810/0/DLF+White+Paper/c774b0aa-4272-446a-1fad-b56ccb047361

Emmanuel Di Pretoro and Friedel Geeraert have self-archived "Behind the Scenes of Web Archiving: Metadata of Harvested Websites."

Here's an excerpt:

This paper first provides more information about web archiving from a technical point of view before focusing on descriptive metadata in the context of web archiving and the WARC file format. Lastly, the experiments done within the PROMISE project with regard to integrating metadata into the WARC file format are discussed.

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

https://doi.org/10.1002/asi.24247

https://sr.ithaka.org/blog/the-usability-of-research-data-if-we-curate-will-they-reuse-it/

Veronica Ikeshoji-Orlati et al. have published "Tiny Data: Building a Community of Practice around Humanities Datasets" in the International Journal of Digital Curation.

Here's an excerpt:

Quantitative data, the foundation of scientific research, have been in the foreground of discussions about data creation, curation, and publication pipelines. However, data for humanistic and social scientific inquiries take many forms, including physical and ephemeral primary resources (books, objects, performances, interactions); qualitative, free-form observations; as well as quantitative, structured data and metadata. At the Vanderbilt University Jean and Alexander Heard Library, we started the Tiny Data Working Group (TDWG) in 2016 to tackle some of the humanistic research data creation and curation issues in a constructive, collaborative, and interdisciplinary format. The present paper considers what it means to be FAIR with humanities data, as well as how to build a community of data-literate humanists, based on our experiences with the TDWG.

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

https://www.forbes.com/sites/kalevleetaru/2019/05/03/we-must-bring-libraries-journalists-and-technologists-together-to-preserve-online-news/

Clara Llebot has published "Remediation Data Management Plans: A Tool for Recovering Research Data from Messy, Messy Projects" in the International Journal of Digital Curation.

Here's an excerpt:

Data Management Plans (DMPs) have been used in the last decade to encourage good data management practices among researchers. DMPs are widely used, preventive tools that encourage good data management practices. DMPs are traditionally used to manage data during the planning stage of the project, often required for grant proposals, and prior to data collection. In this paper we will use a case study to argue that Data Management Plans can be useful in improving the management of the data of research projects that have moved beyond the planning stage of the research life cycle. In particular, we focus on the case of active projects where data has already been collected and is still being analyzed. We discuss the differences and commonalities in structure between preventive Data Management Plans and remedial Data Management Plans, and describe in detail the additional considerations that are needed when writing remedial Data Management Plans: the goals and audience of the document, the data inventory, and an implementation plan.

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

https://dl.acm.org/citation.cfm?id=3300356

https://dpconline.org/our-work/dpeg-home

Priya Deshpande et al. have published "DiiS: A Biomedical Data Access Framework for Aiding Data Driven Research Supporting FAIR Principles " in Data (CC BY 4.0).

Here's an excerpt:

In this paper, we introduce and describe an abstract framework that models these ideal [FAIR] goals, and could be a step toward supporting data driven research. We also develop a system instantiated on our framework called the Data integration and indexing System (DiiS). The system provides an integration model for making healthcare data available on a global scale. Our research work describes the challenges inhibiting data producers, data stewards, and data brokers in achieving FAIR goals for sharing biomedical data. We attempt to address some of the key challenges through the proposed system. We evaluated our framework using the software architecture testing technique and also looked at how different challenges in data integration are addressed by our system. Our evaluation shows that the DiiS framework is a user friendly data integration system that would greatly contribute to biomedical research.

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

https://doi.org/10.1515/pdtc-2018-0036

https://www.degruyter.com/view/j/pdtc.2019.48.issue-1/pdtc-2018-0032/pdtc-2018-0032.xml