Research Data Curation Bibliography
Charles W. Bailey, Jr.
Houston: Digital Scholarship
Version 5: 7/1/2015


The Research Data Curation Bibliography includes over 350 selected English-language articles, books, and technical reports that are useful in understanding the curation of digital research data in academic and other research institutions.

For broader coverage of the digital curation literature, see the author's Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works,which presents over 650 English-language articles, books, and technical reports, and the Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works, 2012 Supplement, which presents over 130 additional sources.

The "digital curation" concept is still evolving. In "Digital Curation and Trusted Repositories: Steps toward Success," Christopher A. Lee and Helen R. Tibbo define digital curation as follows:

Digital curation involves selection and appraisal by creators and archivists; evolving provision of intellectual access; redundant storage; data transformations; and, for some materials, a commitment to long-term preservation. Digital curation is stewardship that provides for the reproducibility and re-use of authentic digital data and other digital assets. Development of trustworthy and durable digital repositories; principles of sound metadata creation and capture; use of open standards for file formats and data encoding; and the promotion of information management literacy are all essential to the longevity of digital resources and the success of curation efforts.

This bibliography does not cover digital media works (such as MP3 files), editorials, e-mail messages, interviews, letters to the editor, presentation slides or transcripts, unpublished e-prints, or weblog postings. Coverage of conference papers and technical reports is very selective.

Most sources have been published from January 2009 through December 2014; however, a limited number of earlier key sources are also included. The bibliography includes links to freely available versions of included works. If such versions are unavailable, links to the publishers' descriptions are provided.

Such links, even to publisher versions and versions in disciplinary archives and institutional repositories, are subject to change. URLs may alter without warning (or automatic forwarding) or they may disappear altogether. Inclusion of links to works on authors' personal websites is highly selective. Note that e prints and published articles may not be identical

Abstracts are included in this bibliography if a work is under a Creative Commons Attribution License (BY and national/international variations), a Creative Commons public domain dedication (CC0), or a Creative Commons Public Domain Mark and this is clearly indicated in the work (see the "Note on the Inclusion of Abstracts" below for more details).

An archive of prior versions of the bibliography is available.


In memory of Paul Evan Peters (1947-1996), founding Executive Director of the Coalition for Networked Information, whose visionary leadership at the dawn of the Internet era fostered the development of scholarly electronic publishing.


Aalbersberg, IJsbrand Jan, Sophia Atzeni, Hylke Koers, Beate Specker, and Elena Zudilova-Seinstra. "Bringing Digital Science Deep Inside the Scientific Article: The Elsevier Article of the Future Project." LIBER Quarterly 23, no. 4 (2014): 275-299.

In 2009, Elsevier introduced the "Article of the Future" project to define an optimal way for the dissemination of science in the digital age, and in this paper we discuss three of its key dimensions. First we discuss interlinking scientific articles and research data stored with domain-specific data repositories—such interlinking is essential to interpret both article and data efficiently and correctly. We then present easy-to-use 3D visualization tools embedded in online articles: a key example of how the digital article format adds value to scientific communication and helps readers to better understand research results. The last topic covered in this paper is automatic enrichment of journal articles through text-mining or other methods. Here we share insights from a recent survey on the question: how can we find a balance between creating valuable contextual links, without sacrificing the high-quality, peer-reviewed status of published articles?

This work is licensed under a Creative Commons Attribution 4.0 License..

Aalbersberg, IJsbrand, Judson Dunham, and Hylke Koers. "Connecting Scientific Articles with Research Data: New Directions in Online Scholarly Publishing." Data Science Journal 12 (2013): WDS235-WDS242.

Researchers across disciplines are increasingly utilizing electronic tools to collect, analyze, and organize data. However, when it comes to publishing their work, there are no common, well-established standards on how to make that data available to other researchers. Consequently, data are often not stored in a consistent manner, making it hard or impossible to find data sets associated with an article—even though such data might be essential to reproduce results or to perform further analysis. Data repositories can play an important role in improving this situation, offering increased visibility, domain-specific coordination, and expert knowledge on data management. As a leading STM publisher, Elsevier is actively pursuing opportunities to establish links between the online scholarly article and data repositories. This helps to increase usage and visibility for both articles and data sets and also adds valuable context to the data. These data-linking efforts tie in with other initiatives at Elsevier to enhance the online article in order to connect with current researchers' workflows and to provide an optimal platform for the communication of science in the digital era.

This work is licensed under a Creative Commons Attribution 3.0 License..

Abrams, Stephen, Patricia Cruse, Carly Strasser, Perry Willet, Geoffrey Boushey, Julia Kochi, Megan Laurance, and Angela Rizk-Jackson. "DataShare: Empowering Researcher Data Curation." International Journal of Digital Curation 9, no. 1 (2014): 110-118.

Researchers are increasingly being asked to ensure that all products of research activity—not just traditional publications—are preserved and made widely available for study and reuse as a precondition for publication or grant funding, or to conform to disciplinary best practices. In order to conform to these requirements, scholars need effective, easy-to-use tools and services for the long-term curation of their research data. The DataShare service, developed at the University of California, is being used by researchers to: (1) prepare for curation by reviewing best practice recommendations for the acquisition or creation of digital research data; (2) select datasets using intuitive file browsing and drag-and-drop interfaces; (3) describe their data for enhanced discoverability in terms of the DataCite metadata schema; (4) preserve their data by uploading to a public access collection in the UC3 Merritt curation repository; (5) cite their data in terms of persistent and globally-resolvable DOI identifiers; (6) expose their data through registration with well-known abstracting and indexing services and major internet search engines; (7) control the dissemination of their data through enforceable data use agreements; and (8) discover and retrieve datasets of interest through a faceted search and browse environment. Since the widespread adoption of effective data management practices is highly dependent on ease of use and integration into existing individual, institutional, and disciplinary workflows, the emphasis throughout the design and implementation of DataShare is to provide the highest level of curation service with the lowest possible technical barriers to entry by individual researchers. By enabling intuitive, self-service access to data curation functions, DataShare helps to contribute to more widespread adoption of good data curation practices that are critical to open scientific inquiry, discourse, and advancement.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Accomazzi, Alberto, Edwin Henneken, Christopher Erdmann, and Arnold Rots."Telescope Bibliographies: An Essential Component of Archival Data Management and Operations." Proceedings of SPIE 8448 (2012): 84480K-1-84480K-10.

Adamick, Jessica, Rebecca C. Reznik-Zellen, and Matt Sheridan. "Data Management Training for Graduate Students at a Large Research University." Journal of eScience Librarianship 1, no. 3 (2013): 180-188.

Adams, Sam, and Peter Murray-Rust. "Chempound—A Web 2.0-Inspired Repository for Physical Science Data." Journal of Digital Information 13, no. 1 (2012).

Akers, Katherine G. "Going Beyond Data Management Planning: Comprehensive Research Data Services." College & Research Libraries News 75, no. 8 (2014): 435-436.

Akers, Katherine G., and Jennifer A. Green. "Towards a Symbiotic Relationship Between Academic Libraries and Disciplinary Data Repositories: A Dryad and University of Michigan Case Study." International Journal of Digital Curation 9, no. 1 (2014): 119-131.

In addition to encouraging the deposit of research data into institutional data repositories, academic librarians can further support research data sharing by facilitating the deposit of data into external disciplinary data repositories.

In this paper, we focus on the University of Michigan Library and Dryad, a repository for scientific and medical data, as a case study to explore possible forms of partnership between academic libraries and disciplinary data repositories. We found that although few University of Michigan researchers have submitted data to Dryad, many have recently published articles in Dryad-integrated journals, suggesting significant opportunities for Dryad use on our campus. We suggest that academic libraries could promote the sharing and preservation of science and medical data by becoming Dryad members, purchasing vouchers to cover researchers' data submission costs, and hosting local curators who could directly work with campus researchers to improve the accuracy and completeness of data packages and thereby increase their potential for re-use.

By enabling the use of both institutional and disciplinary data repositories, we argue that academic librarians can achieve greater success in capturing the vast amounts of data that presently fail to depart researchers' hands and making that data visible to relevant communities of interest.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Akers, Katherine G., Fe C. Sferdean, Natsuko H. Nicholls, and Jennifer A. Green. "Building Support for Research Data Management: Biographies of Eight Research Universities." International Journal of Digital Curation 9, no. 2 (2014): 171-191.

Academic research libraries are quickly developing support for research data management (RDM), including both new services and infrastructure. Here, we tell the stories of how eight different universities have developed programs of RDM support, focusing on the prominent role of the library in educating and assisting researchers with managing their data throughout the research lifecycle. Based on these stories, we construct timelines for each university depicting key steps in building support for RDM, and we discuss similarities and dissimilarities among universities in motivation to provide RDM support, collaborations among campus units, assessment of needs and services, and changes in staffing.

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Akers, Katherine G., and Jennifer Doty. "Disciplinary Differences in Faculty Research Data Management Practices and Perspectives." International Journal of Digital Curation 8, no. 2 (2013): 5-26.

Academic librarians are increasingly engaging in data curation by providing infrastructure (e.g., institutional repositories) and offering services (e.g., data management plan consultations) to support the management of research data on their campuses. Efforts to develop these resources may benefit from a greater understanding of disciplinary differences in research data management needs. After conducting a survey of data management practices and perspectives at our research university, we categorized faculty members into four research domains—arts and humanities, social sciences, medical sciences, and basic sciences—and analyzed variations in their patterns of survey responses. We found statistically significant differences among the four research domains for nearly every survey item, revealing important disciplinary distinctions in data management actions, attitudes, and interest in support services. Serious consideration of both the similarities and dissimilarities among disciplines will help guide academic librarians and other data curation professionals in developing a range of data-management services that can be tailored to the unique needs of different scholarly researchers.

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Akers, Katherine Goold. "Looking Out for the Little Guy: Small Data Curation." Bulletin of the American Society for Information Science and Technology 39, no. 3 (2013): 58-59.

Akmon, Dharma, Ann Zimmerman, Morgan Daniels, and Margaret Hedstrom. "The Application of Archival Concepts to a Data-Intensive Environment: Working with Scientists to Understand Data Management and Preservation Needs." Archival Science 11, no. 3/4 (2011): 329-348.

Albani, Sergio, and David Giaretta. "Long-Term Preservation of Earth Observation Data and Knowledge in ESA through CASPAR." International Journal of Digital Curation 4, no. 3 (2009): 4-16.

Allard, Suzie. "DataONE: Facilitating eScience through Collaboration." Journal of eScience Librarianship 1, no. 1 (2012).

Altman, Micah, and Mercè Crosas. "The Evolution of Data Citation: From Principles to Implementation" IASSIST Quarterly 37, no. 1-4 (2013): 62-70.

Altman, Micah, Margaret O. Adams, Jonathan Crabtree, Darrell Donakowski, Marc Maynard, Amy Pienta, and Copeland H. Young. "Digital Preservation through Archival Collaboration: The Data Preservation Alliance for the Social Sciences." American Archivist 72, no. 1 (2009): 170-184.

Anastasiadis, Stergios V., Syam Gadde, and Jeffrey S. Chase. "Scale and Performance in Semantic Storage Management of Data Grids." International Journal on Digital Libraries 5, no. 2 (2005): 84-98.

Anderson, W. L. "Some Challenges and Issues in Managing, and Preserving Access to, Long Lived Collections of Digital Scientific and Technical Data." Data Science Journal 3 (2004): 191-201.

One goal of the Committee on Data for Science and Technology is to solicit information about, promote discussion of, and support action on the many issues related to scientific and technical data preservation, archiving, and access. This brief paper describes four broad categories of issues that help to organize discussion, learning, and action regarding the work needed to support the long-term preservation of, and access to, scientific and technical data. In each category, some specific issues and areas of concern are described.

This work is licensed under a Creative Commons Attribution 3.0 License.

Androulakis, Steve, Ashley M. Buckle, Ian Atkinson, David Groenewegen, Nick Nicholas, Andrew Treloar, and Anthony Beitz. "ARCHER—e-Research Tools for Research Data Management." International Journal of Digital Curation 4, no. 1 (2009): 22-33.

Angevaare, Inge. "Taking Care of Digital Collections and Data: 'Curation' and Organisational Choices for Research Libraries." LIBER Quarterly: The Journal of European Research Libraries 19, no. 1 (2009): 1-12.

This article explores the types of digital information research libraries typically deal with and what factors might influence libraries' decisions to take on the work of data curation themselves, to take on the responsibility for data but market out the actual work, or to leave the responsibility to other organisations. The article introduces the issues dealt with in the LIBER Workshop 'Curating Research' to be held in The Hague on 17 April 2009 ( and this corresponding issue of LIBER Quarterly.

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Aschenbrenner, Andreas, Harry Enke, Thomas Fischer, and Jens Ludwig. "Diversity and Interoperability of Repositories in a Grid Curation Environment." Journal of Digital Information 12, no. 2 (2011).

Arora, Ritu, Maria Esteva, and Jessica Trelogan. "Leveraging High Performance Computing for Managing Large and Evolving Data Collections." International Journal of Digital Curation 9, no. 2 (2014): 17-27.

The process of developing a digital collection in the context of a research project often involves a pipeline pattern during which data growth, data types, and data authenticity need to be assessed iteratively in relation to the different research steps and in the interest of archiving. Throughout a project's lifecycle curators organize newly generated data while cleaning and integrating legacy data when it exists, and deciding what data will be preserved for the long term. Although these actions should be part of a well-oiled data management workflow, there are practical challenges in doing so if the collection is very large and heterogeneous, or is accessed by several researchers contemporaneously. There is a need for data management solutions that can help curators with efficient and on-demand analyses of their collection so that they remain well-informed about its evolving characteristics. In this paper, we describe our efforts towards developing a workflow to leverage open science High Performance Computing (HPC) resources for routinely and efficiently conducting data management tasks on large collections. We demonstrate that HPC resources and techniques can significantly reduce the time for accomplishing critical data management tasks, and enable a dynamic archiving throughout the research process. We use a large archaeological data collection with a long and complex formation history as our test case. We share our experiences in adopting open science HPC resources for large-scale data management, which entails understanding usage of the open source HPC environment and training users. These experiences can be generalized to meet the needs of other data curators working with large collections.

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Asher, Andrew, and Lori M. Jahnke. "Curating the Ethnographic Moment." Archive Journal, no. 3 (2013).

Ashley, Kevin. "Data Quality and Curation." Data Science Journal 12 (2013): GRDI65-GRDI68.

Data quality is an issue that touches on every aspect of the research data landscape and is therefore appropriate to examine in the context of planning for future research data infrastructures. As producers, researchers want to believe that they produce high quality data; as consumers, they want to obtain data of the highest quality. Data centres typically have stringent controls to ensure that they only acquire and disseminate data of the highest quality. Data managers will usually say that they improve the quality of the data they are responsible for. Much of the infrastructure that will emit, transform, integrate, visualise, manage, analyse, and disseminate data during its life will have dependencies, explicit or implicit, on the quality of the data it is dealing with.

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——— "Research Data And Libraries: Who Does What." Insights: the UKSG Journal 25, no. 2 (2012): 155-157.

A range of external pressures are causing research data management (RDM) to be an increasing concern at senior level in universities and other research institutions. But as well as external pressures, there are also good reasons for establishing effective research data management services within institutions which can bring benefits to researchers, their institutions and those who publish their research. In this article some of these motivating factors, both positive and negative, are described. Ways in which libraries can play a role—or even lead—in the development of RDM services that work within the institution and as part of a national and international research data infrastructure are also set out.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

Bache, Richard, Simon Miles, Bolaji Coker, and Adel Taweel. "Informative Provenance for Repurposed Data: A Case Study using Clinical Research Data." International Journal of Digital Curation 8, no. 2 (2013): 27-46.

The task repurposing of heterogeneous, distributed data for originally unintended research objectives is a non-trivial problem because the mappings required may not be precise. A particular case is clinical data collected for patient care being used for medical research. The fact that research repositories will record data differently means that assumptions must be made as how to transform of this data. Records of provenance that document how this process has taken place will enable users of the data warehouse to utilise the data appropriately and ensure that future data added from another source is transformed using comparable assumptions. For a provenance-based approach to be reusable and supportable with software tools, the provenance records must use a well-defined model of the transformation process. In this paper, we propose such a model, including a classification of the individual 'sub-functions' that make up the overall transformation. This model enables meaningful provenance data to be generated automatically. A case study is used to illustrate this approach and an initial classification of transformations that alter the information is created.

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Baker, Karen S., and Lynn Yarmey. "Data Stewardship: Environmental Data Curation and a Web-of-Repositories." International Journal of Digital Curation 4, no. 2 (2009): 12-27.

Balkestein, Marjan, and Heiko Tjalsma. "The ADA Approach: Retro-archiving Data in an Academic Environment." Archival Science 7, no. 1 (2007): 89-105.

Ball, Alexander, Kevin Ashley, Patrick McCann, Laura Molloy, and Veerle Van den Eynden. "Show Me The Data: The Pilot UK Research Data Registry." International Journal of Digital Curation 9, no. 1 (2014): 132-141.

The UK Research Data (Metadata) Registry (UKRDR) pilot project is implementing a prototype registry for the UK's research data assets, enabling the holdings of subject-based data centres and institutional data repositories alike to be searched from a single location. The purpose of the prototype is to prove the concept of the registry, and uncover challenges that will need to be addressed if and when the registry is developed into a sustainable service. The prototype is being tested using metadata records harvested from nine UK data centres and the data repositories of nine UK universities.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Ball, Alexander, Sean Chen, Jane Greenberg, Cristina Perez, Keith Jeffery, and Rebecca Koskela. "Building a Disciplinary Metadata Standards Directory." International Journal of Digital Curation 9, no. 1 (2014): 142-151.

The Research Data Alliance (RDA) Metadata Standards Directory Working Group (MSDWG) is building a directory of descriptive, discipline-specific metadata standards. The purpose of the directory is to promote the discovery, access and use of such standards, thereby improving the state of research data interoperability and reducing duplicative standards development work.

This work builds upon the UK Digital Curation Centre's Disciplinary Metadata Catalogue, a resource created with much the same aim in mind. The first stage of the MSDWG's work was to update and extend the information contained in the catalogue. In the current, second stage, a new platform is being developed in order to extend the functionality of the directory beyond that of the catalogue, and to make it easier to maintain and sustain. Future work will include making the directory more amenable to use by automated tools.

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Ball, Alexander, Mansur Darlington, Thomas Howard, Chris McMahon, and Steve Culley. "Visualizing Research Data Records for Their Better Management." Journal of Digital Information 13, no. 1 (2012).

Ball, Joanna. "Research Data Management for Libraries: Getting Started." Insights: The UKSG journal 26, no. 3 (2013): 256-260.

Many libraries are keen to take on new roles in providing support for effective research data management (RDM), but lack the necessary skills and resources to do so. This article explores the approach used by the University of Sussex to engage with academic departments about their RDM practices and requirements in order to develop relevant library support services. It describes a project undertaken with three Academic Schools to inform a list of recommendations for senior management, to include areas which should be taken forward by the Library, IT and Research Office in order to create a sustainable RDM service. The article is unflinchingly honest in sharing the differing reactions to the project and the lessons learnt along the way.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

Barateiro, José, Gonçalo Antunes, Manuel Cabral, José Borbinha, and Rodrigo Rodrigues. "Digital Preservation of Scientific Data." Lecture Notes in Computer Science 5173 (2008): 388-391.

———. "Using a Grid for Digital Preservation." Lecture Notes in Computer Science 5362 (2008): 225-235.

Bardi, Alessia, and Paolo Manghi. "Enhanced Publications: Data Models and Information Systems." LIBER Quarterly 23, no. 4 (2014): 240-273.

"Enhanced publications" are commonly intended as digital publications that consist of a mandatory narrative part (the description of the research conducted) plus related "parts", such as datasets, other publications, images, tables, workflows, devices. The state-of-the-art on information systems for enhanced publications has today reached the point where some kind of common understanding is required, in order to provide the methodology and language for scientists to compare, analyse, or simply discuss the multitude of solutions in the field. In this paper, we thoroughly examined the literature with a two-fold aim: firstly, introducing the terminology required to describe and compare structural and semantic features of existing enhanced publication data models; secondly, proposing a classification of enhanced publication information systems based on their main functional goals.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Bardyn, Tania P., Taryn Resnick, and Susan K. Camina. "Translational Researchers' Perceptions of Data Management Practices and Data Curation Needs: Findings from a Focus Group in an Academic Health Sciences Library." Journal of Web Librarianship 6, no. 4 (2012): 274-287.

Baru, Chaitanya. "Sharing and Caring of eScience Data." International Journal on Digital Libraries 7, no. 1/2 (2007): 113-116.

Beagrie, Neil, Robert Beagrie, and Ian Rowlands. "Research Data Preservation and Access: The Views of Researchers." Ariadne, no. 60 (2009).

Beagrie, Neil, Julia Chruszcz, and Brian Lavoie. Keeping Research Data Safe: A Cost Model and Guidance for UK Universities. London: JISC, 2008.

Beagrie, Neil, and John Houghton. The Value and Impact of Data Sharing and Curation: A Synthesis of Three Recent Studies of UK Research Data Centres. London: JISC, 2014.

Beagrie, Neil, Brian Lavoie, and Matthew Woollard. Keeping Research Data Safe 2. London: JISC, 2010.

Beale, Gareth, and Hembo Pagi. Datapool Imaging Case Study: Final Report. Southampton: University of Southampton, 2013.

Beckett, Mark G., Chris R. Allton, Christine T. H. Davies, Ilan Davis, Jonathan M. Flynn, Eilidh J. Grant, Russell S. Hamilton, Alan C. Irving, R. D. Kenway, Radoslaw H. Ostrowski, James T. Perry, Jason R. Swedlow, and Arthur Trew. "Building a Scientific Data Grid with DiGS." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1897 (2009): 2471-2481.

Belter, Christopher W. "Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets." PLOS ONE 9, no. 3 (2014): e92590.

Evaluation of scientific research is becoming increasingly reliant on publication-based bibliometric indicators, which may result in the devaluation of other scientific activities—such as data curation—that do not necessarily result in the production of scientific publications. This issue may undermine the movement to openly share and cite data sets in scientific publications because researchers are unlikely to devote the effort necessary to curate their research data if they are unlikely to receive credit for doing so. This analysis attempts to demonstrate the bibliometric impact of properly curated and openly accessible data sets by attempting to generate citation counts for three data sets archived at the National Oceanographic Data Center. My findings suggest that all three data sets are highly cited, with estimated citation counts in most cases higher than 99% of all the journal articles published in Oceanography during the same years. I also find that methods of citing and referring to these data sets in scientific publications are highly inconsistent, despite the fact that a formal citation format is suggested for each data set. These findings have important implications for developing a data citation format, encouraging researchers to properly curate their research data, and evaluating the bibliometric impact of individuals and institutions.

This work is licensed under a Creative Commons Public Domain Dedication.

Bender, Stefam, and Jorg Heining. "The Research-Data-Centre in Research-Data-Centre Approach: A First Step towards Decentralised International Data Sharing." IASSIST Quarterly 35, no. 3 (2011): 10-16.

Berman, Francine. "Got Data? A Guide to Data Preservation in the Information Age." Communications of the ACM 51, no. 12 (2008): 50-56.

Bethune, Alec, Butch Lazorchak, and Zsolt Nagy. "GeoMAPP: A Geospatial Multistate Archive and Preservation Partnership." Journal of Map & Geography Libraries 6, no. 1 (2009): 45-56.

Bird, Colin L., Cerys Willoughby, Simon J. Coles, and Jeremy G. Frey. "Data Curation Issues in the Chemical Sciences." Information Standards Quarterly 25, no. 3 (2013): 4-12.

Bishop, Bradley Wade, Tony H. Grubesic, and Sonya Prasertong. "Digital Curation and the GeoWeb: An Emerging Role for Geographic Information Librarians." Journal of Map & Geography Libraries: Advances in Geospatial Information, Collections & Archives 9, no. 3 (2013): 296-312.

Borgman, Christine L. "The Conundrum of Sharing Research Data." Journal of the American Society for Information Science and Technology 63, no. 6 (2012): 1059-1078.

Borgman, Christine L., Jillian C. Wallis, and Noel Enyedy. "Little Science Confronts the Data Deluge: Habitat Ecology, Embedded Sensor Networks, and Digital Libraries." International Journal on Digital Libraries 7, no. 1/2 (2007): 17-30.

Bracke, Marianne Stowell. "Emerging Data Curation Roles for Librarians: A Case Study of Agricultural Data." Journal of Agricultural & Food Information 12, no. 1 (2011): 65-74.

Bradić-Martinović, Aleksandra, and Aleksandar Zdravković. "Researchers' Interest in Data Service in Bosnia and Herzegovina, Croatia, and Serbia." IASSIST Quarterly 38, no. 2 (2014): 22-28.

Brandt, D. Scott, and Eugenia Kim. "Data Curation Profiles as a Means to Explore Managing, Sharing, Disseminating or Preserving Digital Outcomes." International Journal of Performance Arts and Digital Media 10, no. 1 (2014): 21-34.

Bresnahan, Megan M., and Andrew M. Johnson. "Assessing Scholarly Communication and Research Data Training Needs." Reference Services Review 41, no. 3 (2013): 413-433.

Broeder, Daan, and Laurence Lannom. "Data Type Registries: A Research Data Alliance Working Group." D-Lib Magazine 20, no. 1/2 (2014).

Brownlee, Rowan. "Research Data and Repository Metadata: Policy and Technical Issues at the University of Sydney Library." Cataloging & Classification Quarterly 47, no. 3/4 (2009): 370-379.

Burton, A., D. Groenewegen, C. Love, A. Treloar, and R. Wilkinson. "Making Research Data Available in Australia." Intelligent Systems 27, no. 3 (2012): 40-43.

Burton, Adrian, and Andrew Treloar. "Designing for Discovery and Re-use: The 'ANDS Data Sharing Verbs' Approach to Service Decomposition." International Journal of Digital Curation 4, no. 3 (2009): 44-56.

Byatt, Dorothy, Federico De Luca, Harry Gibbs, Meriel Patrick, Sally Rumsey, and Wendy White. Supporting Researchers with Their Research Data Management: Professional Service Training Requirements—A DataPool Project Report. Southampton, UK: University of Southampton, 2013.

Through the JISC funded Institutional Research Management Blueprint Project (IDMB) the University of Southampton developed its 10 year blueprint (Brown et al, 2011) for building the required infrastructure. It did this by investigating what researchers were currently doing with their data and what they thought they required. As well as the blueprint, the IDMB project also developed a draft research data management policy to underpin this work. In DataPool: Engaging with our Research Data Management Policy White & Brown (2013) detail how this draft policy was refined and approved. The policy on its own is insufficient but is an important step in enabling the development of the supporting infrastructure, both technological and personnel. The training strand of the DataPool project included an assessment of professional development requirements for staff supporting researchers in managing their data throughout the research life cycle. This report will focus on the investigation undertaken to assess the level of expertise in the relevant support staff groups, identify the training needs of those staff and consider what networks need to be developed to enable collaborative support of researchers in the area of research data management. It will report on the results of the survey carried out at the University of Southampton.

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Byatt, Dorothy, Mark Scott, Gareth Beale, Simon J. Cox, and Wendy White. Developing Researcher Skills in Research Data Management: Training for the Future—A DataPool Project Report. Southampton, UK: University of Southampton, 2013.

This report will look at the multi-level approach to developing researcher skills in research data management in the University of Southampton, developed as part of the training strand of the JISC DataPool project, and embedded into the University engagement with research data management. It will look at how:

  • the multi-level approach to research data management training provides opportunities for cross- and multi-disciplinary sharing events as well as bespoke subject specific sessions;
  • co-delivery with active researchers and/or other professional support services benefits the presentation and relevance of the material to the researchers;
  • focussing the event and matching content to the expected audience is key;
  • using the Institutional Data Management Blueprint dual approach of bottom-up (researchers needs)/top-down (institutional policies and infrastructure) worked

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Byatt, Dorothy, and Wendy White. Research Data Management Planning, Guidance and Support: A DataPool Project Report. Southampton: University of Southampton, 2013.

This report will review the development of research data management support in the University of Southampton following the approval of its research data management policy in February 2012. Wendy White (2013) in her report DataPool: Engaging with our Research Data Management Policy discusses the rationale and approach to the development of the policy. This report will look at the development of the research data management web pages, including the supporting policy guidance, and then will focus on the ResearchData@soton email, phone and desk side service launched to provide research data support to the University.

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Callaghan, Sarah. "Preserving the Integrity of the Scientific Record: Data Citation and Linking." Learned Publishing 27, no. 5 (2014): 15-24.

Callaghan, Sarah, Steve Donegan, Sam Pepler, Mark Thorley, Nathan Cunningham, Peter Kirsch, Linda Ault, Patrick Bell, Rod Bowie, Adam Leadbetter, Roy Lowry, Gwen Moncoiffé, Kate Harrison, Ben Smith-Haddon, Anita Weatherby, and Dan Wright. "Making Data a First Class Scientific Output: Data Citation and Publication by NERC's Environmental Data Centres." International Journal of Digital Curation 7, no. 1 (2012): 107-113.

The NERC Science Information Strategy Data Citation and Publication project aims to develop and formalise a method for formally citing and publishing the datasets stored in its environmental data centres. It is believed that this will act as an incentive for scientists, who often invest a great deal of effort in creating datasets, to submit their data to a suitable data repository where it can properly be archived and curated. Data citation and publication will also provide a mechanism for data producers to receive credit for their work, thereby encouraging them to share their data more freely.

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Callaghan, Sarah, Jonathan Tedds, John Kunze, Varsha Khodiyar, Rebecca Lawrence, Matthew S. Mayernik, Fiona Murphy, Timothy Roberts, and Angus Whyte."Guidelines on Recommending Data Repositories as Partners in Publishing Research Data." International Journal of Digital Curation 9, no. 1 (2014): 152-163.

This document summarises guidelines produced by the UK Jisc-funded PREPARDE data publication project on the key issues of repository accreditation. It aims to lay out the principles and the requirements for data repositories intent on providing a dataset as part of the research record and as part of a research publication. The data publication requirements that repository accreditation may support are rapidly changing, hence this paper is intended as a provocation for further discussion and development in the future.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Carlson, Jake. "Demystifying the Data Interview: Developing a Foundation for Reference Librarians to Talk with Researchers about Their Data." Reference Services Review 40, no. 1 (2012): 7-23.

——— "Opportunities and Barriers for Librarians in Exploring Data: Observations from the Data Curation Profile Workshops." Journal of eScience Librarianship 2, no. 2 (2013).

Carlson, Jake, and Marianne Stowell-Bracke. "Data Management and Sharing from the Perspective of Graduate Students: An Examination of the Culture and Practice at the Water Quality Field Station." portal: Libraries and the Academy 13, no. 4 (2013): 343-361.

Castro, Eleni, and Alex Garnett. "Building a Bridge Between Journal Articles and Research Data: The PKP-Dataverse Integration Project." International Journal of Digital Curation 9, no. 1 (2014): 176-184.

A growing number of funding agencies and international scholarly organizations are requesting that research data be made more openly available to help validate and advance scientific research. Thus, this is an opportune moment for research data repositories to partner with journal editors and publishers in order to simplify and improve data curation and publishing practices. One practical example of this type of cooperation is currently being facilitated by a two year (2012-2014) one million dollar Sloan Foundation grant, integrating two well-established open source systems: the Public Knowledge Project's (PKP) Open Journal Systems (OJS), developed by Stanford University and Simon Fraser University; and Harvard University's Dataverse Network web application, developed by the Institute for Quantitative Social Science (IQSS). To help make this interoperability possible, an OJS Dataverse plugin and Data Deposit API are being developed, which together will allow authors to submit their articles and datasets through an existing journal management interface, while the underlying data are seamlessly deposited into a research data repository, such as the Harvard Dataverse. This practice paper will provide an overview of the project, and a brief exploration of some of the specific challenges to and advantages of this integration.

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Chad, Ken, and Suzanne Enright. "The Research Cycle and Research Data Management (RDM): Innovating Approaches at the University of Westminster." Insights: The UKSG Journal 27, no. 2 (2014): 147-153.

This article presents a case study based on experience of delivering a more joined-up approach to supporting institutional research activity and processes, research data management (RDM) and open access (OA). The result of this small study, undertaken at the University of Westminster in 2013, indicates that a more holistic approach should be adopted, embedding RDM more fully into the wider research management landscape and taking researchers' priorities into consideration. Rapid development of an innovative pilot system followed closely on from a positive engagement with researchers, and today a purpose-built, integrated and fully working set of tools are functioning within the virtual research environment (VRE). This provides a coherent 'thread' to support researchers, doctoral students and professional support staff throughout the research cycle. The article describes the work entailed in more detail, together with the impact achieved so far and what future work is planned.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

Chapple, Michael J. "Speaking the Same Language: Building a Data Governance Program for Institutional Impact." EDUCAUSE Review 48, no. 6 (2013): 14-27.

Chervenaka, Ann, Ian Foster, Carl Kesselman, Charles Salisbury, and Steven Tuecke. "The Data Grid: Towards an Architecture for the Distributed Management and Analysis of Large Scientific Datasets." Journal of Network and Computer Applications 23, no. 3 (2000): 187-200.

Choudhury, G. Sayeed. "Case Study in Data Curation at Johns Hopkins University." Library Trends 57, no. 2 (2008): 211-220.

——— "Data Curation: An Ecological Perspective." College & Research Libraries News 71, no. 4 (2010): 194-196.

Choudhury, Sayeed, Tim DiLauro, Alex Szalay, Ethan Vishniac, Robert J. Hanisch, Julie Steffen, Robert Milkey, Teresa Ehling, and Ray Plante. "Digital Data Preservation for Scholarly Publications in Astronomy." International Journal of Digital Curation 2, no. 2 (2007): 20-30.

Clements, Anna. "Research Information Meets Research Data Management. . . in the Library?" Insights: The UKSG journal 26, no. 3 (2013): 298-304.

Research data management (RDM) is a major priority for many institutions as they struggle to cope with the plethora of pronouncements including funder policies, a G8 statement, REF2020 consultations, all stressing the importance of open data in driving everything from global innovation through to more accountable governance; not to mention the more direct possibility that non-compliance could result in grant income drying up. So, at the coalface, how do we become part of this global movement?

In this article the author explains the approach being taken at the University of St Andrews, building on the research information management infrastructure (data, systems and people) that has evolved since 2006. Continuing to navigate through the rapidly evolving research policy and cultural landscape, they aim to establish services to support their research community as it moves to this 'open by default' requirement of funders and governments.

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Coates, Heather L. "Building Data Services From the Ground Up: Strategies and Resources." Journal of eScience Librarianship 3, no. 1 (2014): Article 5.

Collie, W. Aaron, and Michael Witt. "A Practice and Value Proposal for Doctoral Dissertation Data Curation." International Journal of Digital Curation 6, no. 2 (2011): 165-175.

Collins, Ellen. "Use and Impact of UK Research Data Centres." International Journal of Digital Curation 6, no. 1 (2011): 20-31.

Conway, Esther, David Giaretta, Simon Lambert, and Brian Matthews. "Curating Scientific Research Data for the Long Term: A Preservation Analysis Method in Context." International Journal of Digital Curation 6, no. 2 (2011): 38-52.

Conway, Esther, Brian Matthews, David Giaretta, Simon Lambert, Michael Wilson, and Nick Draper. "Managing Risks in the Preservation of Research Data with Preservation Networks." International Journal of Digital Curation 7, no. 1 (2012): 3-15.

Network modelling provides a framework for the systematic analysis of needs and options for preservation. A number of general strategies can be identified, characterised and applied to many situations; these strategies may be combined to produce robust preservation solutions tailored to the needs of the community and responsive to their environment. This paper provides an overview of this approach. We describe the components of a Preservation Network Model and go on to show how it may be used to plan preservation actions according to the requirements of the particular situation using illustrative examples from scientific archives.

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Conway, Esther, Sam Pepler, Wendy Garland, David Hoope, Fulvio Marelli, Luca Liberti, Emanuela Piervitali, Katrin Molch, Helen Glaves, and Lucio Badiali. "Ensuring the Long Term Impact of Earth Science Data through Data Curation and Preservation." Information Standards Quarterly 25, no. 3 (2013): 28-36.

Corrall, Sheila, Mary Anne Kennan, and Waseem Afzal. "Bibliometrics and Research Data Management Services: Emerging Trends in Library Support for Research." Library Trends 61, no. 3 (2013): 636-674.

Council on Library and Information Resources, ed. Research Data Management: Principles, Practices, and Prospects. Washington, DC: Council on Library and Information Resources, 2013.

Cox, Andrew M., and Stephen Pinfield. "Research Data Management and Libraries: Current Activities and Future Priorities." Journal of Librarianship and Information Science 46 no. 4 (2014): 299-316.

Cox, Andrew M., Eddy Verbaan, and Barbara Sen. "A Spider, an Octopus, or an Animal Just Coming into Existence? Designing a Curriculum for Librarians to Support Research Data Management." Journal of eScience Librarianship 3, no. 1 (2014): Article 2.

Cragin, Melissa H., Carole L. Palmer, Jacob R. Carlson, and Michael Witt. "Data Sharing, Small Science and Institutional Repositories." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1926 (2010): 4023-4038.

Creamer, Andrew, Myrna E. Morales, Javier Crespo, Donna Kafel, and Elaine R. Martin. "An Assessment of Needed Competencies to Promote the Data Curation and Management Librarianship of Health Sciences and Science and Technology Librarians in New England." Journal of eScience Librarianship 1, no. 1 (2012).

Creamer, Andrew T., Myrna E. Morales, Donna Kafel, Javier Crespo, and Elaine R.. Martin. "A Sample of Research Data Curation and Management Courses." Journal of eScience Librarianship 1, no. 2 (2012).

Crosas, Mercè. "A Data Sharing Story." Journal of eScience Librarianship 1, no. 3 (2012): 173-179.

———. "The Dataverse Network: An Open-Source Application for Sharing, Discovering and Preserving Data." D-Lib Magazine 17, no. 1/2 (2011).

Cuevas-Vicenttín, Víctor, Parisa Kianmajd, Bertram Ludäscher, Paolo Missier, Fernando Chirigati, Yaxing Wei, David Koop, and Saumen Dey. "The PBase Scientific Workflow Provenance Repository." International Journal of Digital Curation 9, no. 2 (2014): 28-38.

Scientific workflows and their supporting systems are becoming increasingly popular for compute-intensive and data-intensive scientific experiments. The advantages scientific workflows offer include rapid and easy workflow design, software and data reuse, scalable execution, sharing and collaboration, and other advantages that altogether facilitate "reproducible science". In this context, provenance—information about the origin, context, derivation, ownership, or history of some artifact—plays a key role, since scientists are interested in examining and auditing the results of scientific experiments.

However, in order to perform such analyses on scientific results as part of extended research collaborations, an adequate environment and tools are required. Concretely, the need arises for a repository that will facilitate the sharing of scientific workflows and their associated execution traces in an interoperable manner, also enabling querying and visualization. Furthermore, such functionality should be supported while taking performance and scalability into account.

With this purpose in mind, we introduce PBase: a scientific workflow provenance repository implementing the ProvONE proposed standard, which extends the emerging W3C PROV standard for provenance data with workflow specific concepts. PBase is built on the Neo4j graph database, thus offering capabilities such as declarative and efficient querying. Our experiences demonstrate the power gained by supporting various types of queries for provenance data. In addition, PBase is equipped with a user friendly interface tailored for the visualization of scientific workflow provenance data, making the specification of queries and the interpretation of their results easier and more effective.

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Curdt, Constanze, Dirk Hoffmeister, Guido Waldhoff, Christian Jekel, and Georg Bareth. "Scientific Research Data Management for Soil-Vegetation-Atmosphere Data—The TR32DB." International Journal of Digital Curation 7, no. 2 (2012): 68-80.

The implementation of a scientific research data management system is an important task within long-term, interdisciplinary research projects. Besides sustainable storage of data, including accurate descriptions with metadata, easy and secure exchange and provision of data is necessary, as well as backup and visualisation. The design of such a system poses challenges and problems that need to be solved.

This paper describes the practical experiences gained by the implementation of a scientific research data management system, established in a large, interdisciplinary research project with focus on Soil-Vegetation-Atmosphere Data.

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Dallmeier-Tiessen, Suenje, Mariella Guercio, Robert Darby, Kathrin Gitmans, Simon Lambert, Brian Matthews, Jari Suhonen Salvatore Mele, and Michael Wilson. "Enabling Sharing and Reuse of Scientific Data." New Review of Information Networking 19, no. 1 (2014).

Dallmeier-Tiessen, Sunje, Mariella Guercio, Robert Darby, Kathrin Gitmans, Simon Lambert, Jari Suhonen, and Michael Wilson. Compilation of Results on Drivers and Barriers and New Opportunities. Geneva: Opportunities for Data Exchange, 2012.

Opportunities for Data Exchange (ODE) is a FP7 Project carried out by members of the Alliance for Permanent Access (APA), which is gathering evidence to support strategic investment in the emerging e-Infrastructure for data sharing, re-use and preservation. The ODE Conceptual Model has been developed within the Project to characterise the process of data sharing and the factors which give rise to variations in data sharing for different parties involved. Within the overall Conceptual Model there can be identified models of process, of context, and of drivers, barriers and enablers. The Conceptual Model has been evolved on the basis of existing knowledge and expertise, and draws on research conducted both outside of the ODE Project and in earlier stages of the Project itself (Sections 1-2).

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Dallmeier-Tiessen, Suenje, Mariella Guercio, Heikki Helin, Patricia Herterich, Kirnn Kaur, Artemis Lavasa, Juha Lehtonen, and Riina Salmivalli. Exemplar Good Governance Structures and Data Policies. Dorset, UK: Alliance for Permanent Access, 2014.

Darlington, Jeffrey. "A National Archive of Datasets." Ariadne, no. 39 (2004).

Dearborn, Carly C., Amy J. Barto, and Neal A. Harmeyer. "The Purdue University Research Repository: HUBzero Customization for Dataset Publication and Digital Preservation." OCLC Systems & Services: International Digita Llibrary Perspectives 30, no. 1 (2014): 15-27.

Dehnhard, I., E. Weichselgartner, and G. Krampen. "Researcher's Willingness to Submit Data for Data Sharing: A Case Study on a Data Archive for Psychology." Data Science Journal 12 (2013): 172-180.

Data sharing has gained importance in scientific communities because scientific associations and funding organizations require long term preservation and dissemination of data. To support psychology researchers in data archiving and data sharing, the Leibniz Institute for Psychology Information developed an archiving facility for psychological research data in Germany: PsychData. In this paper we report different types of data requests that were sent to researchers with the aim of building up a sustainable data archive. Resulting response rates were rather low, however, comparable to those published by other authors. Possible reasons for the reluctance of researchers to submit data are discussed.

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Delasalle, Jenny. "Research Data Management at the University of Warwick: Recent Steps towards a Joined-up Approach at a UK University"." LIBREAS. Library Ideas, no. 23 (2013): 97-105.

This paper charts the steps taken and possible ways forward for the University of Warwick in its approach to research data management, providing a typical example of a UK research university's approach in two strands: requirements and support. The UK government approach and funding landscape in relation to research data management provided drivers for the University of Warwick to set requirements and provide support, and examples of good practice at other institutions, support from a central national body (the UK Digital Curation Centre) and learning from other universities' experiences all proved valuable to the University of Warwick. Through interviews with researchers at Warwick, various issues and challenges are revealed: perhaps the biggest immediate challenges for Warwick going forward are overcoming scepticism amongst researchers, overcoming costs, and understanding the implications of involving third party companies in research data management. Building technical infrastructure could sit alongside and beyond those immediate steps and beyond the challenges that face one University are those that affect academia as a whole. Researchers and university administrators need to work together to address the broader challenges, such as the accessibility of data for future use and the reward for researchers who practice data management in exemplary ways, and indeed it may be that a wider, national or international but disciplinary technical infrastructure affects what an individual university needs to achieve. As we take these steps, universities and institutions are all learning from each other.

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Delserone, Leslie M. "At the Watershed: Preparing for Research Data Management and Stewardship at the University of Minnesota Libraries." Library Trends 57, no. 2 (2008): 202-210.

Dietrich, Dianne. "Metadata Management in a Data Staging Repository." Journal of Library Metadata 10, no. 2/3 (2010): 79-98.

Dietrich, Dianne, Trisha Adamus, Alison Miner, and Gail Steinhart. "De-Mystifying the Data Management Requirements of Research Funders." Issues in Science & Technology Librarianship, no. 70 (2012).

Dillo, Ingrid, and Peter Doorn. "The Front Office-Back Office Model: Supporting Research Data Management in the Netherlands." International Journal of Digital Curation 9, no. 2 (2014): 39-46.

High quality and timely data management and secure storage of data, both during and after completion of research, are an essential prerequisite for sharing that data. It is therefore crucial that universities and research institutions themselves formulate a clear policy on data management within their organization. For the implementation of this data management policy, high quality support for researchers and an adequate technical infrastructure are indispensable.

This practice paper will present an overview of the merging federated data infrastructure in the Netherlands with its front office—back office model, as a use case of an efficient and effective national support infrastructure for researchers.

We will elaborate on the stakeholders involved, on the services they offer each other, and on the benefits of this model not only for the front and back offices themselves, but also for the researchers. We will also pay attention to a number of challenges that we are facing, like the implementation of a technical infrastructure for automatic data ingest and integrating access to research data.

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Donnelly, Martin. "The DCC's Institutional Engagements: Raising Research Data Management Capacity in UK Higher Education." Bulletin of the American Society for Information Science and Technology 39, no. 6 (2013): 37-40.

Donnelly, Martin, Sarah Jones, and John W. Pattenden-Fail. "DMP Online: A Demonstration of the Digital Curation Centre's Web-based Tool for Creating, Maintaining and Exporting Data Management Plans." Lecture Notes in Computer Science 6273 (2010): 530-533.

Donnelly, Martin, and Robin North. "The Milieu and the MESSAGE: Talking to Researchers about Data Curation Issues in a Large and Diverse E-Science Project." International Journal of Digital Curation 6, no. 1 (2011): 32-44.

Doty, Jennifer, Joel Herndon, Jared Lyle, and Libbie Stephenson. "Learning to Curate." Bulletin of the American Society for Information Science and Technology 40, no. 6 (2014): 31-34.

Downs, Robert R., and Robert S. Chen. "Designing Submission and Workflow Services for Preserving Interdisciplinary Scientific Data." Earth Science Informatics 3, no. 1/2 (2010): 101-110.

——— "Organizational Needs for Managing and Preserving Geospatial Data and Related Electronic Records." Data Science Journal 4 (2005).

Government agencies and other organizations are required to manage and preserve records that they create and use to facilitate future access and reuse. The increasing use of geospatial data and related electronic records presents new challenges for these organizations, which have relied on traditional practices for managing and preserving records in printed form. This article reports on an investigation of current and future needs for managing and preserving geospatial electronic records on the part of localand state-level organizations in the New York City metropolitan region. It introduces the study and describes organizational needs observed, including needs for organizational coordination and interorganizational cooperation throughout the entire data lifecycle.

This work is licensed under a Creative Commons Attribution 3.0 License.

Duranti, L. "The Long-Term Preservation of Accurate and Authentic Digital Data: The INTERPARES Project." Data Science Journal 4 (2006).

This article presents the InterPARES Project, a multidisciplinary international research initiative aimed at developing the theoretical and methodological knowledge necessary for the long-term preservation of digital entities produced in the course of business or research activity so that their authenticity can be presumed or verified. The methodology, research activities, preliminary findings and projected products are discussed in the context of the issues that the project attempts to address.

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Dürr, Eugène, Kees van der Meer, Wim Luxemburg, and Ronald Dekker. "Dataset Preservation for the Long Term: Results of the DareLux Project." International Journal of Digital Curation 3, no. 1 (2008): 29-43.

Dürr, Eugène, Kees van der Meer, Wim Luxemburg, Maria Heijne, and Ronald Dekker. "Long-Time Preservation of Data Sets, Results of the DareLux Project." Information Services and Use 28, no. 3/4 (2008): 281-294.

Eaker, Christopher. "Planning Data Management Education Initiatives: Process, Feedback, and Future Directions." Journal of eScience Librarianship 3, no. 1 (2014): Article 1.

Erway, Ricky. Starting the Conversation: University-wide Research Data Management Policy Dublin, Ohio OCLC Research, 2013.

This call for action addresses the high-level benefits of adopting a university-wide policy regarding research data management. It identifies the various university stakeholders and suggests that the library initiate a conversation among them in order to get buy-in for a proactive, rather than reactive, high-level policy for responsible data planning and management that is supported and sustainable.

The intended audience for this call for action is library directors, not because they alone can make this happen, but to encourage them to initiate the conversation. They are invested, because the library may be the recipient of data in need of curation and of requests for guidance, but more importantly, library staff have significant skills and experience to contribute to the discussion. This is an opportunity for the library director to play an entrepreneurial role in furthering the mission of the larger enterprise.

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Erwin, Tracey, and Julie Sweetkind-Singer. "The National Geospatial Digital Archive: A Collaborative Project to Archive Geospatial Data." Journal of Map & Geography Libraries 6, no. 1 (2010): 6-25.

Erwin, Tracey, Julie Sweetkind-Singer, and Mary Lynette Larsgaard. "The National Geospatial Digital Archives—Collection Development: Lessons Learned." Library Trends 57, no. 3 (2009): 490-515.

Faniel, Ixchel M., and Ann Zimmerman. "Beyond the Data Deluge: A Research Agenda for Large-Scale Data Sharing and Reuse." International Journal of Digital Curation 6, no. 1 (2011): 58-69.

Fary, Michael, and Kim Owen. Developing an Institutional Research Data Management Plan Service. Louisville, CO: EDUCAUSE, 2013.

Faundeen, John L. "The Challenge of Archiving and Preserving Remotely Sensed Data." Data Science Journal 2 (2003): 159-163.

Few would question the need to archive the scientific and technical (S&T) data generated by researchers. At a minimum, the data are needed for change analysis. Likewise, most people would value efforts to ensure the preservation of the archived S&T data. Future generations will use analysis techniques not even considered today. Until recently, archiving and preserving these data were usually accomplished within existing infrastructures and budgets. As the volume of archived data increases, however, organizations charged with archiving S&T data will be increasingly challenged (U.S. General Accounting Office, 2002). The U.S. Geological Survey has had experience in this area and has developed strategies to deal with the mountain of land remote sensing data currently being managed and the tidal wave of expected new data. The Agency has dealt with archiving issues, such as selection criteria, purging, advisory panels, and data access, and has met with preservation challenges involving photographic and digital media. That experience has allowed the USGS to develop management approaches, which this paper outlines.

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Fear, Kathleen. "'You Made It, You Take Care of It': Data Management as Personal Information Management." International Journal of Digital Curation 6, no. 2 (2011): 53-77.

Fearon, David, Jr., Betsy Gunia, Barbara E. Pralle, Sherry Lake, and Andrew L. Sallans. SPEC Kit 334: Research Data Management Services. Washington, DC: ARL, 2013.

Federer, Lisa. "The Librarian as Research Informationist: A Case Study." Journal of the Medical Library Association 101, no. 4 (2013): 298-302.

Feijen, Martin. What Researchers Want. Utrecht: SURFfoundation, 2011.

In October 2010, the Dutch universities explored po ssible projects in the area of research data. One of the outcomes of this discussion was the decision to first investigate what researchers need with respect to storing and accessing research data . The present literature study is the result of that investigation. Fifteen sources were studied, consisting of reports from 2008-2010 covering the Netherlands, the UK, the USA, Australia and Europe.

This work is licensed under a Creative Commons Attribution 3.0 Netherlands Licence.

Ferguson, Jen. "Description and Annotation of Biomedical Data Sets." Journal of eScience Librarianship 1, no. 1 (2012).

———. "Lurking in the Lab: Analysis of Data from Molecular Biology Laboratory Instruments." Journal of eScience Librarianship 1, no. 3 (2012): 148-158.

Ferreira, Filipe, Miguel E. Coimbra, Raquel Bairrão, Ricardo Viera, Ana T. Freitas, Luís M. S. Russo, and José Borbinha. "Data Management in Metagenomics: A Risk Management Approach." International Journal of Digital Curation 9, no. 1 (2014): 41-56.

In eScience, where vast data collections are processed in scientific workflows, new risks and challenges are emerging. Those challenges are changing the eScience paradigm, mainly regarding digital preservation and scientific workflows. To address specific concerns with data management in these scenarios, the concept of the Data Management Plan was established, serving as a tool for enabling digital preservation in eScience research projects. We claim risk management can be jointly used with a Data Management Plan, so new risks and challenges can be easily tackled. Therefore, we propose an analysis process for eScience projects using a Data Management Plan and ISO 31000 in order to create a Risk Management Plan that can complement the Data Management Plan. The motivation, requirements and validation of this proposal are explored in the MetaGen-FRAME project, focused in Metagenomics.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Finney, K. "Managing Antarctic Data—A Practical Use Case." Data Science Journal 13 (2014): PDA8-PDA14.

Scientific data management is performed to ensure that data are curated in a manner that supports their qualified reuse. Curation usually involves actions that must be performed by those who capture or generate data and by a facility with the capability to sustainably archive and publish data beyond an individual project's lifecycle. The Australian Antarctic Data Centre is such a facility. How this centre is approaching the administration of Antarctic science data is described in the following paper and serves to demonstrate key facets necessary for undertaking polar data management in an increasingly connected global data environment.

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Fox, Robert. "The Art and Science of Data Curation." OCLC Systems & Services: International Digita Llibrary Perspectives 29, no. 4 (2013): 195-199.

Frey, Jeremy. "Curation of Laboratory Experimental Data as Part of the Overall Data Lifecycle." International Journal of Digital Curation 3, no. 1 (2008): 44-62.

Friddell, J., E. LeDrew, and W. Vincent. "The Polar Data Catalogue: Best Practices for Sharing and Archiving Canada's Polar Data." Data Science Journal 13 (2014): PDA1-PDA7.

The Polar Data Catalogue (PDC) is a growing Canadian archive and public access portal for Arctic and Antarctic research and monitoring data. In partnership with a variety of Canadian and international multi-sector research programs, the PDC encompasses the natural, social, and health sciences. From its inception, the PDC has adopted international standards and best practices to provide a robust infrastructure for reliable security, storage, discoverability, and access to Canada's polar data and metadata. Current efforts focus on developing new partnerships and incentives for data archiving and sharing and on expanding connections to other data centres through metadata interoperability protocols.

This work is licensed under a Creative Commons Attribution 3.0 License.

Frisz, Chris, Geoffrey Brown, and Samuel Waggoner. "Assessing Migration Risk for Scientific Data Formats." International Journal of Digital Curation 7, no. 1 (2012): 27-38.

The majority of information about science, culture, society, economy and the environment is born digital, yet the underlying technology is subject to rapid obsolescence. One solution to this obsolescence, format migration, is widely practiced and supported by many software packages, yet migration has well known risks. For example, newer formats—even where similar in function —do not generally support all of the features of their predecessors, and, where similar features exist, there may be significant differences of interpretation.

There appears to be a conflict between the wide use of migration and its known risks. In this paper we explore a simple hypothesis—that, where migration paths exist, the majority of data files can be safely migrated leaving only a few that must be handled more carefully—in the context of several scientific data formats that are or were widely used. Our approach is to gather information about potential migration mismatches and, using custom tools, evaluate a large collection of data files for the incidence of these risks. Our results support our initial hypothesis, though with some caveats. Further, we found that writing a tool to identify "risky" format features is considerably easier than writing a migration tool.

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Gabridge, Tracy. "The Last Mile: Liaison Roles in Curating Science and Engineering Research Data." Research Library Issues: A Bimonthly Report from ARL, CNI, AND SPARC, no. 265 (2009): 15-21.

Ganley, Emma. "PLOS Data Policy: Catalyst for a Better Research Process." College & Research Libraries News 75, no. 6 (2014): 305-308.

Garrett, Leigh, Marie-Therese Gramstadt, and Carlos Silva. " Here, KAPTUR This! Identifying and Selecting the Infrastructure Required to Support the Curation and Preservation of Visual Arts Research Data." International Journal of Digital Curation 8, no. 2 (2013): 68-88.

Research data is increasingly perceived as a valuable resource and, with appropriate curation and preservation, it has much to offer learning, teaching, research, knowledge transfer and consultancy activities in the visual arts. However, very little is known about the curation and preservation of this data: none of the specialist arts institutions have research data management policies or infrastructure and anecdotal evidence suggests that practice is ad hoc, left to individual researchers and teams with little support or guidance. In addition, the curation and preservation of such diverse and complex digital resources as found in the visual arts is, in itself, challenging. Led by the Visual Arts Data Service, a research centre of the University for the Creative Arts, in collaboration with the Glasgow School of Art; Goldsmiths College, University of London; and University of the Arts London, and funded by JISC, the KAPTUR project (2011-2013) seeks to address the lack of awareness and explore the potential of research data management systems in the arts by discovering the nature of research data in the visual arts, investigating the current state of research data management, developing a model of best practice applicable to both specialist arts institutions and arts departments in multidisciplinary institutions, and by applying, testing and piloting the model with the four institutional partners. Utilising the findings of the KAPTUR user requirement and technical review, this paper will outline the method and selection of an appropriate research data management system for the visual arts and the issues the team encountered along the way.

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Garrett, Leigh, Marie-Therese Gramstadt, Carlos Silva, and Anne Spalding. "KAPTUR the Highlights: Exploring Research Data Management in the Visual Arts." Ariadne, no. 71 (2013).

Gaudette, Glenn R., and Donna Kafel. "A Case Study: Data Management in Biomedical Engineering." Journal of eScience Librarianship 1, no. 3 (2012): 159-172.

Gelernter, Judith, and Michael Lesk. "Use of Ontologies for Data Integration and Curation." International Journal of Digital Curation 6, no. 1 (2011).

Getler, Magdalena, Diana Sisu, Sarah Jones, and Kerry Miller. "DMPonline Version 4.0: User-Led Innovation." International Journal of Digital Curation 9, no. 1 (2014): 193-219.

DMPonline is a web-based tool to help researchers and research support staff produce data management and sharing plans. Between October and December 2012, we examined DMPonline in unprecedented detail. The results of this evaluation led to some major changes. We have shortened the DCC Checklist for a Data Management Plan and revised how this is used in the tool. We have also amended the data model for DMPonline, improved workflows and redesigned the user interface.

This paper reports on the evaluation, outlining the methods used, the results gathered and how they have been acted upon. We conducted usability testing on v.3 of DMPonline and the v.4 beta prior to release. The results from these two rounds of usability testing are compared to validate the changes made. We also put forward future plans for a more iterative development approach and greater community input.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Giarlo, Michael J. "Academic Libraries as Data Quality Hubs." Journal of Librarianship and Scholarly Communication 1, no. 3 (2013): eP1059.

Academic libraries have a critical role to play as data quality hubs on campus. There is an increased need to ensure data quality within 'e-science'. Given academic libraries' curation and preservation expertise, libraries are well suited to support the data quality process. Data quality measurements are discussed, including the fundamental elements of trust, authenticity, understandability, usability and integrity, and are applied to the Digital Curation Lifecycle model to demonstrate how these measures can be used to understand and evaluate data quality within the curatorial process. Opportunities for improvement and challenges are identified as areas that are fruitful for future research and exploration.

This work is licensed under a Creative Commons Creative Commons Attribution 3.0 License.

Goben, Abigail, and Dorothea Salo. "Federal Research Data Requirements Set to Change." College & Research Libraries News 74, no. 8 (2013): 421-425.

Greenberg, Jane. "Metadata for Scientific Data: Historical Considerations, Current Practice, and Prospects." Journal of Library Metadata 10, no. 2/3 (2010): 75-78.

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Griffiths, Aaron. "The Publication of Research Data: Researcher Attitudes and Behaviour." International Journal of Digital Curation 4, no. 1 (2009): 46-56.

Groenewegen, David, and Andrew Treloar. "Adding Value by Taking a National and Institutional Approach to Research Data: The ANDS Experience." International Journal of Digital Curation 8, no. 2 (2013): 89-98.

The Australian National Data Service (ANDS) has been working to add value to Australia's research data environment since 2009. This paper looks at the changes that have occurred over this time, ANDS' role in those changes and the current state of the Australian research sector at this time, using case studies of selected institutions.

This work is licensed under a Creative Commons Attribution License.

Grootveld, Marjan, and Jeff van Egmond. "Peer-Reviewed Open Research Data: Results of a Pilot." International Journal of Digital Curation 7, no. 2 (2012): 81-91.

Peer review of publications is at the core of science and primarily seen as instrument for ensuring research quality. However, it is less common to independently value the quality of the underlying data as well. In the light of the 'data deluge' it makes sense to extend peer review to the data itself and this way evaluate the degree to which the data are fit for re-use. This paper describes a pilot study at EASY—the electronic archive for (open) research data at our institution. In EASY, researchers can archive their data and add metadata themselves. Devoted to open access and data sharing, at the archive we are interested in further enriching these metadata with peer reviews.

As a pilot, we established a workflow where researchers who have downloaded data sets from the archive were asked to review the downloaded data set. This paper describes the details of the pilot including the findings, both quantitative and qualitative. Finally, we discuss issues that need to be solved when such a pilot is turned into a structural peer review functionality for the archiving system.

This work is licensed under a Creative Commons Attribution License.

Gutmann, M., K. Schürer, D. Donakowski, and Hilary Beedham. "The Selection, Appraisal, and Retention of Social Science Data." Data Science Journal 3 (2004): 209-221.

The number of data collections produced in the social sciences prohibits the archiving of every scientific study. It is therefore necessary to make decisions regarding what can be preserved and why it should be preserved. This paper reviews the processes used by two data archives, one from the United States and one from the United Kingdom, to illustrate how data are selected for archiving, how they are appraised, and what steps are required to retain the usefulness of the data for future use. It also presents new initiatives that seek to encourage an increase in the long-term preservation of digital resources.

This work is licensed under a Creative Commons Attribution 3.0 License.

Gutmann, Myron P., Mark Abrahamson, Margaret O. Adams, Micah Altman, Caroline Arms, Kenneth Bollen, Michael Carlson, Jonathan Crabtree, Darrell Donakowski, Gary King, Jared Lyle, Marc Maynard, Amy Pienta, Richard Rockwell, Lois Timms-Ferrara, and Copeland H. Young. "From Preserving the Past to Preserving the Future: The Data-PASS Project and the Challenges of Preserving Digital Social Science Data." Library Trends 57, no. 3 (2009): 315-337.

Guy, Marieke, Martin Donnelly, and Laura Molloy. "Pinning It Down: Towards a Practical Definition of 'Research Data' for Creative Arts Institutions." International Journal of Digital Curation 8, no. 2 (2013): 99-110.

There is a widespread understanding among scientific researchers about what is meant by 'research data'; however this does not readily translate into a creative context. As part of its engagement with the University of the Arts London (UAL) and via its support for the JISC Managing Research Data Programme, the Digital Curation Centre (DCC) and partners have worked towards an acceptable and practical definition of research data for creative arts institutions. This paper describes the activities carried out to help pin down such a definition, including a literature review, short and extended interviews with researchers, interactions with an academic arts research practitioner, and distillation of the results from a one-day workshop which took place in London in September 2012.

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Halbert, Martin. " The Problematic Future of Research Data Management: Challenges, Opportunities and Emerging Patterns Identified by the DataRes Project." International Journal of Digital Curation 8, no. 2 (2013): 111-122.

This paper describes findings and projections from a project that has examined emerging policies and practices in the United States regarding the long-term institutional management of research data. The DataRes project at the University of North Texas (UNT) studied institutional transitions taking place during 2011-2012 in response to new mandates from U.S. governmental funding agencies requiring research data management plans to be submitted with grant proposals. Additional synergistic findings from another UNT project, termed iCAMP, will also be reported briefly.

This paper will build on these data analysis activities to discuss conclusions and prospects for likely developments within coming years based on the trends surfaced in this work. Several of these conclusions and prospects are surprising, representing both opportunities and troubling challenges, for not only the library profession but the academic research community as a whole.

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——— "Shedding Light on the Dark Data in the Long Tail of Science." Library Trends 57, no. 2 (2008): 280-299.

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This paper reviews developments in funders' data management and sharing policies, and explores the extent to which they have affected practice. The Digital Curation Centre has been monitoring UK research funders' data policies since 2008. There have been significant developments in subsequent years, most notably the joint Research Councils UK's Common Principles on Data Policy and the Engineering and Physical Sciences Research Council's Policy Framework on Research Data. This paper charts these changes and highlights shifting emphasises in the policies. Institutional data policies and infrastructure are increasingly being developed as a result of these changes. While action is clearly being taken, questions remain about whether the changes are affecting practice on the ground.

This work is licensed under a Creative Commons Attribution License.

Jones, Sarah, Alexander Ball, and Çuna Ekmekcioglu. "The Data Audit Framework: A First Step in the Data Management Challenge." International Journal of Digital Curation 3, no. 2 (2008): 112-120.

Jones, Sarah, Graham Pryor, and Angus Whyte. How to Develop Research Data Management Services—A Guide for HEIs. Edinburgh: Digital Curation Centre, 2013.

The purpose of this guide is to help institutions understand the key aims and issues associated with planning and implementing research data management (RDM) services. It explains the components and processes of RDM services and describes the roles and responsibilities of those who will deliver and use them.

This work is licensed under a Creative Commons Creative Commons Attribution 2.5 Scotland License.

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We present a case study of data integration and reuse involving 12 researchers who published datasets in Open Context, an online data publishing platform, as part of collaborative archaeological research on early domesticated animals in Anatolia. Our discussion reports on how different editorial and collaborative review processes improved data documentation and quality, and created ontology annotations needed for comparative analyses by domain specialists. To prepare data for shared analysis, this project adapted editor-supervised review and revision processes familiar to conventional publishing, as well as more novel models of revision adapted from open source software development of public version control. Preparing the datasets for publication and analysis required significant investment of effort and expertise, including archaeological domain knowledge and familiarity with key ontologies. To organize this work effectively, we emphasized these different models of collaboration at various stages of this data publication and analysis project. Collaboration first centered on data editors working with data contributors, then widened to include other researchers who provided additional peer-review feedback, and finally the widest research community, whose collaboration is facilitated by GitHub's version control system. We demonstrate that the "publish" and "push" models of data dissemination need not be mutually exclusive; on the contrary, they can play complementary roles in sharing high quality data in support of research. This work highlights the value of combining multiple models in different stages of data dissemination.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

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This report sets out the current thinking on data citation best practice and presents the results of a survey of librarians asking how new support roles could and should be developed. The findings presented here build on the extensive desk research carried out for the report "Integration of Data and Publication" (Reilly, Schallier, Schrimpf, Smit, & Wilkinson, Sept 2011), which identified that data citation was an area of opportunity for both researchers and libraries. That report also recounted the findings of a workshop held at the LIBER 2011 Conference in Barcelona. The workshop, based on preliminary findings on the integration of data and publications, revealed that, although libraries saw the emerging research data landscape as an opportunity, there was a real need to define future directions and the scope of the role of libraries in data exchange. The issue of data citation was also identified as a fundamental issue to be addressed when exploring the way forward. This previous work is supported here with further information gathered through extensive desk research, structured interviews and an online survey of LIBER members to explore best practice in data citation and evolving support roles for libraries.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

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The movement to bring datasets into the scholarly record as first class research products (validated, preserved, cited, and credited) has been inching forward for some time, but now the pace is quickening. As data publication venues proliferate, significant debate continues over formats, processes, and terminology. Here, we present an overview of data publication initiatives underway and the current conversation, highlighting points of consensus and issues still in contention. Data publication implementations differ in a variety of factors, including the kind of documentation, the location of the documentation relative to the data, and how the data is validated. Publishers may present data as supplemental material to a journal article, with a descriptive "data paper," or independently. Complicating the situation, different initiatives and communities use the same terms to refer to distinct but overlapping concepts. For instance, the term published means that the data is publicly available and citable to virtually everyone, but it may or may not imply that the data has been peer-reviewed. In turn, what is meant by data peer review is far from defined; standards and processes encompass the full range employed in reviewing the literature, plus some novel variations. Basic data citation is a point of consensus, but the general agreement on the core elements of a dataset citation frays if the data is dynamic or part of a larger set. Even as data publication is being defined, some are looking past publication to other metaphors, notably "data as software," for solutions to the more stubborn problems.

This work is licensed under a Creative Commons Attribution 4.0 International License.

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The amount of research data is growing constantly, due to new technology with new potentials for collecting and analysing both digital data and research objects. This growth creates a demand for a coherent IT-infrastructure. Such an infrastructure must be able to provide facilities for storage, preservation and a more open access to data in order to fulfil the demands from the researchers themselves, the research councils and research foundations.

This paper presents the findings of a research project carried out under the auspices of DEFF (Danmarks Elektroniske Fag- og Forskningsbibliotek—Denmark's Electronic research Library)[i] to analyse how the Danish universities store, preserve and provide access to research data. It shows that they do not have a common IT-infrastructure for research data management. This paper describes the various paths chosen by individual universities and research institutions, and the background for their strategies of research data management. Among the main reasons for the uneven practices are the lack of a national policy in this field, the different scientific traditions and cultures and the differences in the use and organization of IT-services.

This development contains several perspectives that are of particular relevance to research libraries. As they already curate digital collections and are active in establishing web archives, the research libraries become involved in research and dissemination of knowledge in new ways. This paper gives examples of how The State and University Library's services facilitate research data management with special regard to digitization of research objects, storage, preservation and sharing of research data. This paper concludes that the experience and skills of research libraries make the libraries important partners in a research data management infrastructure.

This work is licensed under a Creative Commons Attribution 4.0 License.

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In this paper we describe eBird, a highly successful citizen science project. With over 150,000 participants worldwide and an accumulation of over 140,000,000 bird observations globally in the last decade, eBird has evolved into a major tool for scientific investigations in diverse fields such as ornithology, computer science, statistics, ecology and climate change. eBird's impact in scientific research is grounded in careful data curation practices that pay attention to all stages of the data lifecycle, and attend to the needs of stakeholders engaged in that data lifecycle. We describe the important aspects of eBird, paying particular attention to the mechanisms to improve data quality; describe the data products that are available to the global community; investigate some aspects of the downloading community; and demonstrate significant results that derive from the use of openly-available eBird data.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

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The value of data in society is increasing rapidly. Organisations that work with data should have standard practices in place to ensure successful curation of data. The World Data System (WDS) consists of a number of data centres responsible for curating research data sets for the scientific community. The WDS has no formal data curation framework or model in place to act as a guideline for member data centres. The objective of this research was to develop a framework for the curation of data in the WDS. A multiple-case case study was conducted. Interviews were used to gather qualitative data and analysis of the data, which led to the development of this framework. The proposed framework is largely based on the Open Archival Information System (OAIS) functional model and caters for the curation of both analogue and digital data.

This work is licensed under a Creative Commons Attribution 3.0 License.

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In the vision of Global Research Data Infrastructures (GRDIs), data storage and management plays a crucial role. A successful GRDI will require a common globally interoperable distributed data system, formed out of data centres, that incorporates emerging technologies and new scientific data activities. The main challenge is to define common certification and auditing frameworks that will allow storage providers and data communities to build a viable partnership based on trust. To achieve this, it is necessary to find a long-term commitment model that will give financial, legal, and organisational guarantees of digital information preservation. In this article we discuss the state of the art in data storage and management for GRDIs and point out future research directions that need to be tackled to implement GRDIs.

This work is licensed under a Creative Commons Attribution 3.0 License.

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Scientific workflows are typically used to automate the processing, analysis and management of scientific data. Most scientific workflow programs provide a user-friendly graphical user interface that enables scientists to more easily create and visualize complex workflows that may be comprised of dozens of processing and analytical steps. Furthermore, many workflows provide mechanisms for tracing provenance and methodologies that foster reproducible science. Despite their potential for enabling science, few studies have examined how the process of creating, executing, and sharing workflows can be improved. In order to promote open discourse and access to scientific methods as well as data, we analyzed a wide variety of workflow systems and publicly available workflows on the public repository myExperiment. It is hoped that understanding the usage of workflows and developing a set of recommended best practices will lead to increased contribution of workflows to the public domain.

This work is licensed under a Creative Commons Attribution License.

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In this paper, Liz Lyon explores how libraries can re-shape to better reflect the requirements and challenges of today's data-centric research landscape. The Informatics Transform presents five assertions as potential pathways to change, which will help libraries to re-position, re-profile, and re-structure to better address research data management challenges. The paper deconstructs the institutional research lifecycle and describes a portfolio of ten data support services which libraries can deliver to support the research lifecycle phases. Institutional roles and responsibilities for research data management are also unpacked, building on the framework from the earlier Dealing with Data Report. Finally, the paper examines critical capacity and capability challenges and proposes some innovative steps to addressing the significant skills gaps.

This work is licensed under a Creative Commons Attribution License.

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Among the key services that institutional data management infrastructures must provide are provenance and lineage tracking and the ability to associate data with contextual information needed for understanding and use. These functionalities are critical for addressing a number of key issues faced by data collectors and users, including trust in data, results traceability, data transparency, and data citation support. In this paper, we describe the support for these services within the Data Conservancy Service (DCS) software. The DCS provenance, context, and lineage services cross the four layers in the DCS data curation stack model: storage, archiving, preservation, and curation.

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McLure, Merinda, Allison V. Level, Catherine L. Cranston, Beth Oehlert, and Mike Culbertson. "Data Curation: A Study of Researcher Practices and Needs." portal: Libraries and the Academy 14, no. 2 (2014).

McNally, Ruth, Adrian Mackenzie, Allison Hui, and Jennifer Tomomitsu. "Understanding the 'Intensive' in 'Data Intensive Research': Data Flows in Next Generation Sequencing and Environmental Networked Sensors." International Journal of Digital Curation 7, no. 1 (2012): 81-94.

Genomic and environmental sciences represent two poles of scientific data. In the first, highly parallel sequencing facilities generate large quantities of sequence data. In the latter, loosely networked remote and field sensors produce intermittent streams of different data types. Yet both genomic and environmental sciences are said to be moving to data intensive research. This paper explores and contrasts data flow in these two domains in order to better understand how data intensive research is being done. Our case studies are next generation sequencing for genomics and environmental networked sensors.

Our objective was to enrich understanding of the 'intensive' processes and properties of data intensive research through a 'sociology' of data using methods that capture the relational properties of data flows. Our key methodological innovation was the staging of events for practitioners with different kinds of expertise in data intensive research to participate in the collective annotation of visual forms. Through such events we built a substantial digital data archive of our own that we then analysed in terms of three traits of data flow: durability, replicability and metrology.

Our findings are that analysing data flow with respect to these three traits provides better insight into how doing data intensive research involves people, infrastructures, practices, things, knowledge and institutions. Collectively, these elements shape the topography of data and condition how it flows. We argue that although much attention is given to phenomena such as the scale, volume and speed of data in data intensive research, these are measures of what we call 'extensive' properties rather than intensive ones. Our thesis is that extensive changes, that is to say those that result in non-linear changes in metrics, can be seen to result from intensive changes that bring multiple, disparate flows into confluence.

If extensive shifts in the modalities of data flow do indeed come from the alignment of disparate things, as we suggest, then we advocate the staging of workshops and other events with the purpose of developing the 'missing' metrics of data flow.

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Medeiros, Norm. "A Public Trust: Libraries and Data Curation " OCLC Systems & Services: International Digita Llibrary Perspectives 29, no. 4 (2013): 192-194.

Meghini, Carlo. "Data Preservation." Data Science Journal 12 (2013): GRDI51-GRDI57.

Digital information is a vital resource in our knowledge economy, valuable for research and education, science and the humanities, creative and cultural activities, and public policy (The Blue Ribbon Task Force on Sustainable Digital Preservation and Access, 2010). New high-throughput instruments, telescopes, satellites, accelerators, supercomputers, sensor networks, and running simulations are generating massive amounts of data (Thanos, 2011). These data are used by decision makers for improving the quality of life of citizens. Moreover, researchers are employing sophisticated technologies to analyse these data to address questions that were unapproachable just a few years ago (Helbing & Balietti, 2011). Digital technologies have fostered a new world of research characterized by immense datasets, unprecedented levels of openness among researchers, and new connections among researchers, policy makers, and the public (The National Academy of Sciences, 2009).

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Michener, William, Todd Vision, Patricia Cruse, Dave Vieglais, John Kunze, and Greg Janée. "DataONE: Data Observation Network for Earth—Preserving Data and Enabling Innovation in the Biological and Environmental Sciences." D-Lib Magazine 17, no. 1/2 (2011).

Minor, David, Matt Critchlow, Arwen Hutt, Declan Fleming, Mary Linn Bergstrom, and Don Sutton. "Research Data Curation Pilots: Lessons Learned." International Journal of Digital Curation 9, no. 1 (2014): 220-230.

In the spring of 2011, the UC San Diego Research Cyberinfrastructure (RCI) Implementation Team invited researchers and research teams to participate in a research curation and data management pilot program. This invitation took the form of a campus-wide solicitation. More than two dozen applications were received and, after due deliberation, the RCI Oversight Committee selected five curation-intensive projects. These projects were chosen based on a number of criteria, including how they represented campus research, varieties of topics, researcher engagement, and the various services required. The pilot process began in September 2011, and will be completed in early 2014. Extensive lessons learned from the pilots are being compiled and are being used in the on-going design and implementation of the permanent Research Data Curation Program in the UC San Diego Library.

In this paper, we present specific implementation details of these various services, as well as lessons learned. The program focused on many aspects of contemporary scholarship, including data creation and storage, description and metadata creation, citation and publication, and long term preservation and access. Based on the lessons learned in our processes, the Research Data Curation Program will provide a suite of services from which campus users can pick and choose, as necessary. The program will provide support for the data management requirements from national funding agencies.

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Minor, David, Don Sutton, Ardys Kozbial, Brad Westbrook, Michael Burek, and Michael Smorul. "Chronopolis Digital Preservation Network." International Journal of Digital Curation 5, no. 1 (2010).

Mischo, William H., Mary C. Schlembach, and Megan N. O'Donnell. "An Analysis of Data Management Plans in University of Illinois National Science Foundation Grant Proposals." Journal of eScience Librarianship 3, no. 1 (2014) Article 3.

Miksa, Tomasz, Stephan Strodl, and Andreas Rauber. "Process Management Plans." International Journal of Digital Curation 9, no. 1 (2014): 83-97.

In the era of research infrastructures and big data, sophisticated data management practices are becoming essential building blocks of successful science. Most practices follow a data-centric approach, which does not take into account the processes that created, analysed and presented the data. This fact limits the possibilities for reliable verification of results. Furthermore, it does not guarantee the reuse of research, which is one of the key aspects of credible data-driven science. For that reason, we propose the introduction of the new concept of Process Management Plans, which focus on the identification, description, sharing and preservation of the entire scientific processes. They enable verification and later reuse of result data and processes of scientific experiments. In this paper we describe the structure and explain the novelty of Process Management Plans by showing in what way they complement existing Data Management Plans. We also highlight key differences, major advantages, as well as references to tools and solutions that can facilitate the introduction of Process Management Plans.

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Missier, Paolo, Bertram Ludäscher, Saumen Dey, Michael Wang, Tim McPhillips, Shawn Bowers, Michael Agun, and Ilkay Altintas. "Golden Trail: Retrieving the Data History That Matters from a Comprehensive Provenance Repository." International Journal of Digital Curation 7, no. 1 (2012): 139-150.

Experimental science can be thought of as the exploration of a large research space, in search of a few valuable results. While it is this "Golden Data" that gets published, the history of the exploration is often as valuable to the scientists as some of its outcomes. We envision an e-research infrastructure that is capable of systematically and automatically recording such history—an assumption that holds today for a number of workflow management systems routinely used in e-science. In keeping with our gold rush metaphor, the provenance of a valuable result is a "Golden Trail". Logically, this represents a detailed account of how the Golden Data was arrived at, and technically it is a sub-graph in the much larger graph of provenance traces that collectively tell the story of the entire research (or of some of it).

In this paper we describe a model and architecture for a repository dedicated to storing provenance traces and selectively retrieving Golden Trails from it. As traces from multiple experiments over long periods of time are accommodated, the trails may be sub-graphs of one trace, or they may be the logical representation of a virtual experiment obtained by joining together traces that share common data.

The project has been carried out within the Provenance Working Group of the Data Observation Network for Earth (DataONE) NSF project. Ultimately, our longer-term plan is to integrate the provenance repository into the data preservation architecture currently being developed by DataONE.

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Mitchell, Erik T. "Research Support: The New Mission for Libraries." Journal of Web Librarianship 7, no. 1 (2013): 109-113.

Molloy, Laura. "DigitalCuration Skills in the Performing Arts—An Investigation of Practitioner Awareness and Knowledge of Digital Object Management and Preservation." International Journal of Performance Arts and Digital Media 10, no. 1 (2014): 7-20.

Molloy, Laura, Ann Gow, and Leo Konstantelos. "The DigCurV Curriculum Framework for Digital Curation in the Cultural Heritage Sector." International Journal of Digital Curation 9, no. 1 (2014): 231-241.

In 2013, the DigCurV collaborative network completed development of a Curriculum Framework for digital curation skills in the European cultural heritage sector.

DigCurV synthesised a variety of established skills and competence models in the digital curation and LIS sectors with expertise from digital curation professionals, in order to develop a new Curriculum Framework. The resulting Framework provides a common language and helps define the skills, knowledge and abilities that are necessary for the development of digital curation training; for benchmarking existing programmes; and for promoting the continuing production, improvement and refinement of digital curation training programmes.

This paper describes the salient points of this work, including how the project team conducted the research necessary to develop the Framework, the structure of the Framework, the processes used to validate the Framework, and three 'lenses' onto the Framework. The paper also provides suggestions as to how the Framework might be used, including a description of potential audiences and purposes.

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Molloy, Laura, Simon Hodson, Meik Poschen, and Jonathan Tedds. "Gathering Evidence of Benefits: A Structured Approach from the JISC Managing Research Data Programme." International Journal of Digital Curation 8, no. 2 (2013): 123-133.

The work of the Jisc Managing Research Data programme is—along with the rest of the UK higher education sector—taking place in an environment of increasing pressure on research funding. In order to justify the investment made by Jisc in this activity—and to help make the case more widely for the value of investing time and money in research data management—individual projects and the programme as a whole must be able to clearly express the resultant benefits to the host institutions and to the broader sector. This paper describes a structured approach to the measurement and description of benefits provided by the work of these projects for the benefit of funders, institutions and researchers. We outline the context of the programme and its work; discuss the drivers and challenges of gathering evidence of benefits; specify benefits as distinct from aims and outputs; present emerging findings and the types of metrics and other evidence which projects have provided; explain the value of gathering evidence in a structured way to demonstrate benefits generated by work in this field; and share lessons learned from progress to date.

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Molloy, Laura, and Kellie Snow. "The Data Management Skills Support Initiative: Synthesising Postgraduate Training in Research Data Management." International Journal of Digital Curation 7, no. 2 (2012): 101-109.

This paper will describe the efforts and findings of the JISC Data Management Skills Support Initiative ('DaMSSI'). DaMSSI was co-funded by the JISC Managing Research Data programme and the Research Information Network (RIN), in partnership with the Digital Curation Centre, to review, synthesise and augment the training offerings of the JISC Research Data Management Training Materials ('RDMTrain') projects.

DaMSSI tested the effectiveness of the Society of College, National and University Libraries' Seven Pillars of Information Literacy model (SCONUL, 2011), and Vitae's Researcher Development Framework ('Vitae RDF') for consistently describing research data management ('RDM') skills and skills development paths in UK HEI postgraduate courses.

With the collaboration of the RDMTrain projects, we mapped individual course modules to these two models and identified basic generic data management skills alongside discipline-specific requirements. A synthesis of the training outputs of the projects was then carried out, which further investigated the generic versus discipline-specific considerations and other successful approaches to training that had been identified as a result of the projects' work. In addition we produced a series of career profiles to help illustrate the fact that data management is an essential component—in obvious and not-so-obvious ways—of a wide range of professions.

We found that both models had potential for consistently and coherently describing data management skills training and embedding this within broader institutional postgraduate curricula. However, we feel that additional discipline-specific references to data management skills could also be beneficial for effective use of these models. Our synthesis work identified that the majority of core skills were generic across disciplines at the postgraduate level, with the discipline-specific approach showing its value in engaging the audience and providing context for the generic principles.

Findings were fed back to SCONUL and Vitae to help in the refinement of their respective models, and we are working with a number of other projects, such as the DCC and the EC-funded Digital Curator Vocational Education Europe (DigCurV2) initiative, to investigate ways to take forward the training profiling work we have begun.

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Moon, Jeff. "Developing a Research Data Management Service—A Case Study " Partnership: the Canadian Journal of Library and Information Practice and Research 9, no. 1 (2014).

Mooney, Hailey. "A Practical Approach to Data Citation: The Special Interest Group on Data Citation and Development of the Quick Guide to Data Citation." IASSIST Quarterly 37, 1-4 (2013): 71-77.

Mooney, Hailey, and Mark P. Newton. "The Anatomy of a Data Citation: Discovery, Reuse, and Credit." Journal of Librarianship and Scholarly Communication 1, no. 1 (2012).

INTRODUCTION Data citation should be a necessary corollary of data publication and reuse. Many researchers are reluctant to share their data, yet they are increasingly encouraged to do just that. Reward structures must be in place to encourage data publication, and citation is the appropriate tool for scholarly acknowledgment. Data citation also allows for the identification, retrieval, replication, and verification of data underlying published studies. METHODS This study examines author behavior and sources of instruction in disciplinary and cultural norms for writing style and citation via a content analysis of journal articles, author instructions, style manuals, and data publishers. Instances of data citation are benchmarked against a Data Citation Adequacy Index. RESULTS Roughly half of journals point toward a style manual that addresses data citation, but the majority of journal articles failed to include an adequate citation to data used in secondary analysis studies. DISCUSSION Full citation of data is not currently a normative behavior in scholarly writing. Multiplicity of data types and lack of awareness regarding existing standards contribute to the problem. CONCLUSION Citations for data must be promoted as an essential component of data publication, sharing, and reuse. Despite confounding factors, librarians and information professionals are well-positioned and should persist in advancing data citation as a normative practice across domains. Doing so promotes a value proposition for data sharing and secondary research broadly, thereby accelerating the pace of scientific research.

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Moore, Reagan W. "Building Preservation Environments with Data Grid Technology." American Archivist 69, no. 1 (2007): 139-158.

———. "Geospatial Web Services and Geoarchiving: New Opportunities and Challenges in Geographic Information Service." Library Trends 55, no. 2 (2006): 285-303.

Morris, Steven. Issues in the Appraisal and Selection of Geospatial Data. Washington, DC: National Digital Stewardship Alliance, 2013.

This paper proposes a series of appraisal and selection recommended practices regarding data relevancy, documentation, currency, research and application needs, usability, risk and ease of acquisition that will help organizations make the initial steps to initiate a digital stewardship plan for geospatial information that touches on each point of the information lifecycle.

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———. "The North Carolina Geospatial Data Archiving Project: Challenges and Initial Outcomes." Journal of Map & Geography Libraries 6, no. 1 (2009): 26-44.

Morris, Steven, James Tuttle, and Jefferson Essic. "A Partnership Framework for Geospatial Data Preservation in North Carolina." Library Trends 57, no. 3 (2009): 516-540.

Murillo, Angela P. "Data at Risk Initiative: Examining and Facilitating the Scientific Process in Relation to Endangered Data." Data Science Journal 12 (2014): 207-219

Examining the scientific process in relation to endangered data, data reuse, and sharing is crucial in facilitating scientific workflow. Deterioration, format obsolescence, and insufficient metadata for discovery are significant problems leading to loss of scientific data. The research presented in this paper considers these potentially lost data. Four one-hour focus groups and a demographic survey were conducted with 14 scientists to learn about their attitudes toward endangered data, data sharing, data reuse, and their opinions of the DARI inventory. The results indicate that unavailability, lack of context, accessibility issues, and potential endangerment are key concerns to scientists.

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Murphy, Fiona. "Data and Scholarly Publishing: The Transforming Landscape." Learned Publishing 27, no. 5 (2014): 3-7.

Musgrave, Simon. "Improving Access to Recorded Language Data." D-Lib Magazine 20, no. 1/2 (2014).

National Academy of Sciences Committee on Ensuring the Utility and Integrity of Research Data in a Digital Age. Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age. Washington, DC: National Academies Press, 2009.

National Research Council Committee on Archiving and Accessing Environmental and Geospatial Data at NOAA. Environmental Data Management at NOAA: Archiving, Stewardship, and Access. Washington, DC: National Academies Press, 2007.

National Science Board. Long-Lived Digital Data Collections Enabling Research and Education in the 21st Century. Washington, DC: National Science Foundation, 2005.

Neuroth, Heike, Felix Lohmeier, and Kathleen Marie Smith. "TextGrid—Virtual Research Environment for the Humanities." International Journal of Digital Curation 6, no. 2 (2011): 222-231.

Nicholl, Natsuko H., Sara M. Samuel, Leena N. Lalwani, Paul F. Grochowski, and Jennifer A. Green. "Resources to Support Faculty Writing Data Management Plans: Lessons Learned from an Engineering Pilot." International Journal of Digital Curation 9, no. 1 (2014): 242-252.

Recent years have seen a growing emphasis on the need for improved management of research data. Academic libraries have begun to articulate the conceptual foundations, roles, and responsibilities involved in data management planning and implementation. This paper provides an overview of the Engineering data support pilot at the University of Michigan Library as part of developing new data services and infrastructure. Through this pilot project, a team of librarians had an opportunity to identify areas where the library can play a role in assisting researchers with data management, and has put forth proposals for immediate steps that the library can take in this regard. The paper summarizes key findings from a faculty survey and discusses lessons learned from an analysis of data management plans from accepted NSF proposals. A key feature of this Engineering pilot project was to ensure that these study results will provide a foundation for librarians to educate and assist researchers with managing their data throughout the research lifecycle.

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Nicholson, Shawn W., and Terrence B. Bennett. "Data Sharing: Academic Libraries and the Scholarly Enterprise." portal: Libraries and the Academy 11, no. 1 (2011): 505-516.

Nielsen, Hans Jørn, and Birger Hjørland. "Curating Research Data: The Potential Roles of Libraries and Information Professionals." Journal of Documentation 70, no. 2 (2014): 221-240.

Norman, Belinda, and Kate Valentine Stanton. "From Project to Strategic Vision: Taking the Lead in Research Data Management Support at the University of Sydney Library." International Journal of Digital Curation 9, no. 1 (2014): 253-262.

This paper explores three stories, each occurring a year apart, illustrating an evolution toward a strategic vision for Library leadership in supporting research data management at the University of Sydney. The three stories describe activities undertaken throughout the Seeding the Commons project and beyond, as the establishment of ongoing roles and responsibilities transition the Library from project partner to strategic leader in the delivery of research data management support. Each story exposes key ingredients that characterise research data management support: researcher engagement; partnerships; and the complementary roles of policy and practice.

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Norman, Hazel. "Mandating Data Archiving: Experiences from the Frontline." Learned Publishing 27, no. 5 (2014): 35-38.

Ogburn, Joyce L. "The Imperative for Data Curation." portal: Libraries & the Academy 10, no. 2 (2010): 241-246.

Olendorf, Robert, and Steve Koch. "Beyond the Low Hanging Fruit: Data Services and Archiving at the University of New Mexico." Journal of Digital Information 13, no. 1 (2012).

O'Malley, Donna L. "Gaining Traction in Research Data Management Support: A Case Study." Journal of eScience Librarianship 3, no. 1 (2014): Article 9.

Oostdijk, Nelleke, Henk van den Heuvel, and Maaske Treurniet. "The CLARIN-NL Data Curation Service: Bringing Data to the Foreground." International Journal of Digital Curation 8, no. 2 (2013): 134-145.

After decades in which a great deal of effort was spent on the creation of resources, there are currently several initiatives worldwide that aim to create an interoperable, sustainable research infrastructure. An integral part of such an infrastructure constitutes the resources (data and tools) which researchers in the various disciplines employ. Whether the infrastructure will be successful in supporting the needs of the research communities it intends to cater for depends on a number of factors. One factor is that resources that are or could be relevant to the wider research community are made visible through this infrastructure and, to the greatest extent possible, accessible and usable. In practice, the durable availability of resources is often not properly regulated within research projects.

CLARIN-NL is directed at creating an interoperable language resources infrastructure for the humanities in the Netherlands. The Data Curation Service was established in order to salvage language resources in this field that are threatened to be lost. In the CLARIN context, a great deal of attention is given to standards, formats and intellectual property rights. Consequently, the Data Curation Service (DCS) has a role as mediator in bringing researchers in the field of humanities and existing data centres closer together.

This article consists of two parts: the first part provides the background to the work of the DCS while the second part illustrates the work of the DCS by describing the actual curation of a collection of language learner data.

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Palaiologk, Anna S., Anastasios A. Economides, Heiko D. Tjalsma, and Laurents B. Sesink. "An Activity-Based Costing Model for Long-Term Preservation and Dissemination of Digital Research Data: The Case of DANS." International Journal on Digital Libraries 12, no. 4 (2012): 195-214.

Palmer, Carole L., Bryan P. Heidorn, Dan Wright, and Melissa H. Cragin. "Graduate Curriculum for Biological Information Specialists: A Key to Integration of Scale in Biology." International Journal of Digital Curation 2, no. 2 (2007): 31-40.

Palmer, Carole L., Nicholas M. Weber, Trevor Muñoz, and Allen H. Renear. "Foundations of Data Curation: The Pedagogy and Practice of 'Purposeful Work' with Research Data." Archive Journal, no. 3 (2013).

Papineau, Diane, and Butch Lazorchak. Geospatial Data Stewardship: Key Online Resources. Washington, DC: National Digital Stewardship Alliance, 2014.

This document lists online resources that highlight key concepts and practices supporting the preservation and stewardship of digital geospatial data and information. GIS practitioners take the initial preservation actions in the decisions they make regarding data creation and management. Librarians, archivists and museum professionals are often called on to support access and the long-term historical and temporal analysis of these same materials. The resources below offer a starting point to methods, tools and approaches across the information lifecycle to assist in understanding current best practices in the stewardship of geospatial data. These resources will be regularly updated at

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Parham, Susan Wells, Jon Bodnar, and Sara Fuchs. "Supporting Tomorrow's Research: Assessing Faculty Data Curation Needs at Georgia Tech " College & Research Libraries News 73, no. 1 (2012): 10-13.

Parsons, M., and P. Fox. "Is Data Publication the Right Metaphor?" Data Science Journal 12 (2013): WDS32-WDS46.

International attention to scientific data continues to grow. Opportunities emerge to re-visit long-standing approaches to managing data and to critically examine new capabilities. We describe the cognitive importance of metaphor. We describe several metaphors for managing, sharing, and stewarding data and examine their strengths and weaknesses. We particularly question the applicability of a "publication" approach to making data broadly available. Our preliminary conclusions are that no one metaphor satisfies enough key data system attributes and that multiple metaphors need to co-exist in support of a healthy data ecosystem. We close with proposed research questions and a call for continued discussion.

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Parsons, Mark A. "Organizational Status of RDA." D-Lib Magazine 20, no. 1/2 (2014).

———. "The Research Data Alliance: Implementing the Technology, Practice and Connections of a Data Infrastructure." Bulletin of the American Society for Information Science and Technology 39, no. 6 (2013): 33-36.

Parsons, Thomas. "Creating a Research Data Management Service." International Journal of Digital Curation 8, no. 2 (2013): 146-156.

This paper provides an overview of the elements required to create a sustainable research data management (RDM) service. The paper summarises key learning and lessons learnt from the University of Nottingham's project to create an RDM service for researchers. Collective experiences and learning from three key areas are covered, including: data management requirements gathering and validation, RDM training, and the creation of an RDM website.

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Parsons, Thomas, Shirley Grimshaw, and Laurian Williamson. Research Data Management Survey: Report. Nottingham, UK: University of Nottingham, 2013.

Partlo, Kristin. "From Data to the Creation of Meaning Part II: Data Librarian as Translator." IASSIST Quarterly 38, no. 2 (2014): 12-15.

Patel, Manjula, and Alexander Ball. "Challenges and Issues Relating to the Use of Representation Information for the Digital Curation of Crystallography and Engineering Data." International Journal of Digital Curation 3, no. 1 (2008): 76-88.

Peer, Limor, and Ann Green. "Building an Open Data Repository for a Specialized Research Community: Process, Challenges and Lessons." International Journal of Digital Curation 7, no. 1 (2012): 151-162.

In 2009, the Institution for Social and Policy Studies (ISPS) at Yale University began building an open access digital collection of social science experimental data, metadata, and associated files produced by ISPS researchers. The digital repository was created to support the replication of research findings and to enable further data analysis and instruction. Content is submitted to a rigorous process of quality assessment and normalization, including transformation of statistical code into R, an open source statistical software. Other requirements included: (a) that the repository be integrated with the current database of publications and projects publicly available on the ISPS website; (b) that it offered open access to datasets, documentation, and statistical software program files; (c) that it utilized persistent linking services and redundant storage provided within the Yale Digital Commons infrastructure; and (d) that it operated in accordance with the prevailing standards of the digital preservation community. In partnership with Yale's Office of Digital Assets and Infrastructure (ODAI), the ISPS Data Archive was launched in the fall of 2010. We describe the process of creating the repository, discuss prospects for similar projects in the future, and explain how this specialized repository fits into the larger digital landscape at Yale.

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Peer, Limor, Ann Green, and Elizabeth Stephenson. "Committing to Data Quality Review." International Journal of Digital Curation 9, no. 1 (2014): 263-291.

Amid the pressure and enthusiasm for researchers to share data, a rapidly growing number of tools and services have emerged. What do we know about the quality of these data? Why does quality matter? And who should be responsible for data quality? We believe an essential measure of data quality is the ability to engage in informed reuse, which requires that data are independently understandable. In practice, this means that data must undergo quality review, a process whereby data and associated files are assessed and required actions are taken to ensure files are independently understandable for informed reuse. This paper explains what we mean by data quality review, what measures can be applied to it, and how it is practiced in three domain-specific archives. We explore a selection of other data repositories in the research data ecosystem, as well as the roles of researchers, academic libraries, and scholarly journals in regard to their application of data quality measures in practice. We end with thoughts about the need to commit to data quality and who might be able to take on those tasks.

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Pejša, Stanislav, Shirley J. Dyke, and Thomas J. Hacker. "Building Infrastructure for Preservation and Publication of Earthquake Engineering Research Data." International Journal of Digital Curation 9, no. 2 (2014): 83-97.

The objective of this paper is to showcase the progress of the earthquake engineering community during a decade-long effort supported by the National Science Foundation in the George E. Brown Jr., Network for Earthquake Engineering Simulation (NEES). During the four years that NEES network operations have been headquartered at Purdue University, the NEEScomm management team has facilitated an unprecedented cultural change in the ways research is performed in earthquake engineering. NEES has not only played a major role in advancing the cyberinfrastructure required for transformative engineering research, but NEES research outcomes are making an impact by contributing to safer structures throughout the USA and abroad. This paper reflects on some of the developments and initiatives that helped instil change in the ways that the earthquake engineering and tsunami community share and reuse data and collaborate in general.

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Peters, Christie, and Porcia Vaughn. "Initiating Data Management Instruction to Graduate Students at the University of Houston Using the New England Collaborative Data Management Curriculum." Journal of eScience Librarianship 3, no. 1 (2014): Article 11.

Pinfield,Stephen, Andrew M. Cox, and Jen Smith. "Research Data Management and Libraries: Relationships, Activities, Drivers and Influences." PLOS ONE 9, no. 12 (2014): e114734.

The management of research data is now a major challenge for research organisations. Vast quantities of born-digital data are being produced in a wide variety of forms at a rapid rate in universities. This paper analyses the contribution of academic libraries to research data management (RDM) in the wider institutional context. In particular it: examines the roles and relationships involved in RDM, identifies the main components of an RDM programme, evaluates the major drivers for RDM activities, and analyses the key factors influencing the shape of RDM developments. The study is written from the perspective of library professionals, analysing data from 26 semi-structured interviews of library staff from different UK institutions. This is an early qualitative contribution to the topic complementing existing quantitative and case study approaches. Results show that although libraries are playing a significant role in RDM, there is uncertainty and variation in the relationship with other stakeholders such as IT services and research support offices. Current emphases in RDM programmes are on developments of policies and guidelines, with some early work on technology infrastructures and support services. Drivers for developments include storage, security, quality, compliance, preservation, and sharing with libraries associated most closely with the last three. The paper also highlights a 'jurisdictional' driver in which libraries are claiming a role in this space. A wide range of factors, including governance, resourcing and skills, are identified as influencing ongoing developments. From the analysis, a model is constructed designed to capture the main aspects of an institutional RDM programme. This model helps to clarify the different issues involved in RDM, identifying layers of activity, multiple stakeholders and drivers, and a large number of factors influencing the implementation of any initiative. Institutions may usefully benchmark their activities against the data and model in order to inform ongoing RDM activity.

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Pink, Catherine. "Meeting the Data Management Compliance Challenge: Funder Expectations and Institutional Reality." International Journal of Digital Curation 8, no. 2 (2013): 157-171.

In common with many global research funding agencies, in 2011 the UK Engineering and Physical Sciences Research Council (EPSRC) published its Policy Framework on Research Data along with a mandate that institutions be fully compliant with the policy by May 2015. The University of Bath has a strong applied science and engineering research focus and, as such, the EPSRC is a major funder of the university's research. In this paper, the Jisc-funded Research360 project shares its experience in developing the infrastructure required to enable a research-intensive institution to achieve full compliance with a particular funder's policy, in such a way as to support the varied data management needs of both the University of Bath and its external stakeholders. A key feature of the Research360 project was to ensure that after the project's completion in summer 2013 the newly developed data management infrastructure would be maintained up to and beyond the EPSRC's 2015 deadline. Central to these plans was the 'University of Bath Roadmap for EPSRC', which was identified as an exemplar response by the EPSRC. This paper explores how a roadmap designed to meet a single funder's requirements can be compatible with the strategic goals of an institution. Also discussed is how the project worked with Charles Beagrie Ltd to develop a supporting business case, thus ensuring implementation of these long-term objectives. This paper describes how two new data management roles, the Institutional Data Scientist and Technical Data Coordinator, have contributed to delivery of the Research360 project and the importance of these new types of cross-institutional roles for embedding a new data management infrastructure within an institution. Finally, the experience of developing a new institutional data policy is shared. This policy represents a particular example of the need to reconcile a funder's expectations with the needs of individual researchers and their collaborators.

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Piorun, Mary E., Donna Kafel, Tracey Leger-Hornby, Siamak Najafi, Elaine R. Martin, Paul Colombo, and Nancy R. LaPelle. "Teaching Research Data Management: An Undergraduate/Graduate Curriculum." Journal of eScience Librarianship 1, no. 1 (2012).

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Major research universities are grappling with their response to the deluge of scientific data emerging through research by their faculty. Many are looking to their libraries and the institutional repositories for a solution. Scientific data introduces substantial challenges that the document-based institutional repository may not be suited to deal with. The Sustainable Environment-Actionable Data (SEAD) Virtual Archive (VA) specifically addresses the challenges of 'long tail' scientific data. In this paper, we propose requirements, policy and architecture to support not only the preservation of scientific data today using institutional repositories, but also rich access to data and their use into the future.

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———. "A Maturing Process of Engagement: Raising Data Capabilities in UK Higher Education." International Journal of Digital Curation 8, no. 2 (2013): 181-193.

In the spring of 2011, the UK's Digital Curation Centre (DCC) commenced a programme of outreach designed to assist individual universities in their development of aptitude for managing research data. This paper describes the approaches taken, covering the context in which these institutional engagements have been discharged and examining the aims, methodology and processes employed. It also explores what has worked and why, as well as the pitfalls encountered, including example outcomes and identifiable or predicted impact. Observing how the research data landscape is constantly undergoing change, the paper concludes with an indication of the steps being taken to refit the DCC institutional engagement to the evolving needs of higher education.

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——— "Multi-Scale Data Sharing in the Life Sciences: Some Lessons for Policy Makers." International Journal of Digital Curation 4, no. 3 (2009): 71-82.

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Scholarly communication is the foundation of modern research where empirical evidence is interpreted and communicated as published hypothesis driven research. Many current and recent reports highlight the impact of advancing technology on modern research and consequences this has on scholarly communication. As part of the ODE project this report sought to coalesce current though and opinions from numerous and diverse sources to reveal opportunities for supporting a more connected and integrated scholarly record. Four perspectives were considered, those of the Researcher who generates or reuses primary data, Publishers who provide the mechanisms to communicate research activities and Libraries & Data enters who maintain and preserve the evidence that underpins scholarly communication and the published record. This report finds the landscape fragmented and comple, where competing interests can sometimes confuse and confound requirements, needs and e,pect ations. Equally the report identifies clear opportunity for all stakeholders to directly enable a more joined up and vital scholarly record of modern research.

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Renear, Allen H., Carole L. Palmer, and John Unsworth. Extending Data Curation to the Humanities: Curiculum Development and Recruiting. Urbana-Champaign: Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign, 2013.

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Rice, Robin, Çuna Ekmekcioglu, Jeff Haywood, Sarah Jones, Stuart Lewis, Stuart Macdonald, and Tony Weir. "Implementing the Research Data Management Policy: University of Edinburgh Roadmap." International Journal of Digital Curation 8, no. 2 (2013): 194-204.

This paper discusses work to implement the University of Edinburgh Research Data Management (RDM) policy by developing the services needed to support researchers and fulfil obligations within a changing national and international setting. This is framed by an evolving Research Data Management Roadmap and includes a governance model that ensures cooperation amongst Information Services (IS) managers and oversight by an academic-led steering group. IS has taken requirements from research groups and IT professionals, and at the request of the steering group has conducted pilot work involving volunteer research units within the three colleges to develop functionality and presentation for the key services. The first pilots cover three key services: the data store, a customisation of the Digital Curation Centre's DMPonline tool, and the data repository. The paper will report on the plans, achievements and challenges encountered while we attempt to bring the University of Edinburgh RDM Roadmap to fruition.

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Rice, Robin, and Jeff Haywood. "Research Data Management Initiatives at University of Edinburgh." International Journal of Digital Curation 6, no. 2 (2011): 232-244.

Richards, Julian D. "Digital Preservation and Access." European Journal of Archaeology 5, no. 3 (2002): 343-366.

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An increasing number of publishers and funding agencies require public data archiving (PDA) in open-access databases. PDA has obvious group benefits for the scientific community, but many researchers are reluctant to share their data publicly because of real or perceived individual costs. Improving participation in PDA will require lowering costs and/or in-creasing benefits for primary data collectors. Small, simple changes can enhance existing measures to ensure that more scientific data are properly archived and made publicly available: (1) facilitate more flexible embargoes on archived data, (2) encourage communication between data generators and re-users, (3) disclose data re-use ethics, and (4) encourage increased recognition of publicly archived data.

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Rumsey, Sally, and Neil Jefferies. "Challenges in Building an Institutional Research Data Catalogue." International Journal of Digital Curation 8, no. 2 (2013): 205-214.

The University of Oxford is preparing systems and services to enable members of the university to manage research data produced by its scholars. Much of the work has been carried out under the Jisc-funded Damaro project. This project draws together existing nascent services, adds new systems and services to 'fill the gaps' and provides a wide-ranging infrastructure. Development comprises four parallel strands: endorsement of a university research data management policy; training and guidance in research data management; technical infrastructure; and future sustainability. A key element of the technical infrastructure is DataFinder, a catalogue of Oxford research data outputs. DataFinder's core purposes are to record the existence of Oxford datasets, enable their discovery, and provide details of their location. DataFinder will record metadata about Oxford research data, irrespective of location, discipline or format, and is viewed by the university as a crucial hub for the university's Research Data Management (RDM) infrastructure.

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———. "DataFinder: A Research Data Catalogue for Oxford." Ariadne, no. 71 (2013).

Sallans, Andrew, and Martin Donnelly. "DMP Online and DMPTool: Different Strategies towards a Shared Goal." International Journal of Digital Curation 7, no. 2 (2012): 123-129.

This paper provides a comparative discussion of the strategies employed in the UK's DMP Online tool and the US's DMPTool, both designed to provide a structured environment for research data management planning (DMP) with explicit links to funder requirements. Following the Sixth International Digital Curation Conference, held in Chicago in December 2010, a number of US institutions partnered with the Digital Curation Centre's DMP Online team to learn from their experiences while developing a US counterpart. DMPTool arrived in beta in August 2011 and released a production version in November 2011. This joint paper will compare and contrast use cases, organizational and national/cultural characteristics that have influenced the development decisions, outcomes achieved so far, and planned future developments.

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Sands, Ashley E., Christine L. Borgman, Sharon Traweek, and Laura A. Wynholds. "We're Working On It: Transferring the Sloan Digital Sky Survey from Laboratory to Library." International Journal of Digital Curation 9, no. 2 (2014): 98-110.

This article reports on the transfer of a massive scientific dataset from a national laboratory to a university library, and from one kind of workforce to another. We use the transfer of the Sloan Digital Sky Survey (SDSS) archive to examine the emergence of a new workforce for scientific research data management. Many individuals with diverse educational backgrounds and domain experience are involved in SDSS data management: domain scientists, computer scientists, software and systems engineers, programmers, and librarians. These types of positions have been described using terms such as research technologist, data scientist, e-science professional, data curator, and more. The findings reported here are based on semi-structured interviews, ethnographic participant observation, and archival studies from 2011-2013.

The library staff conducting the data storage and archiving of the SDSS archive faced two performance problems. The preservation specialist and the system administrator worked together closely to discover and implement solutions to the slow data transfer and verification processes. The team overcame these slow-downs by problem solving, working in a team, and writing code. The library team lacked the astronomy domain knowledge necessary to meet some of their preservation and curation goals.

The case study reveals the variety of expertise, experience, and individuals essential to the SDSS data management process. A variety of backgrounds and educational histories emerge in the data managers studied. Teamwork is necessary to bring disparate expertise together, especially between those with technical and domain education. The findings have implications for data management education, policy and relevant stakeholders.

This article is part of continuing research on Knowledge Infrastructures.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

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Schopfel, Joachim, Stéphane Chaudiron, Bernard Jacquemin, Hélène Prost, Marta Severo, and Florence Thiault. "Open Access to Research Data in Electronic Theses and Dissertations: An Overview." Library Hi Tech 32, no. 4 (2014): 612-627.

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This paper describes initial experiences in evaluating an established data archive with a long-standing commitment to preservation and dissemination of social science research data against recently formulated standards for trustworthy digital archives. As stakeholders need to be sure that the data they produce, use or fund is treated according to common standards, the GESIS Data Archive decided to start a process of audit and certification within the European Framework of Certification and Audit, starting with the Data Seal of Approval (DSA). This paper gives an overview of workflows within the archive and illustrates some of the steps necessary to obtain the DSA as well as to optimize some of its services. Finally, a short appraisal of the method of the DSA is made.

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Schumann, Natascha, and Astrid Recker. "De-mystifying OAIS compliance: Benefits and Challenges of Mapping the OAIS Reference Model to the GESIS Data Archive." IASSIST Quarterly 36, no. 2 (2012): 6-11.

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This paper presents the findings, lessons learned and next steps associated with the implementation of the immersiveInformatics pilot: a distinctive research data management (RDM) training programme designed in collaboration between UKOLN Informatics and the Library at the University of Melbourne, Australia. The pilot aimed to equip a broad range of academic and professional staff roles with RDM skills as a key element of capacity and capability building within a single institution.

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Shaffer, Christopher J. "The Role of the Library in the Research Enterprise." Journal of eScience Librarianship 2, no. 1 (2013): 8-15.

Shaon, Arif, Sarah Callaghan, Bryan Lawrence, Brian Matthews, Timothy Osborn, Colin Harpham, and Andrew Woolf. "Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance." International Journal of Digital Curation 7, no. 1 (2012): 163-173.

Traditionally, the formal scientific output in most fields of natural science has been limited to peer-reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the representation and verification of the data provenance to the confines of the related publications. Detailed knowledge of a dataset's provenance is essential to establish the pedigree of the data for its effective re-use, and to avoid redundant re-enactment of the experiment or computation involved. It is increasingly important for open-access data to determine their authenticity and quality, especially considering the growing volumes of datasets appearing in the public domain. To address these issues, we present an approach that combines the Digital Object Identifier (DOI)—a widely adopted citation technique—with existing, widely adopted climate science data standards to formally publish detailed provenance of a climate research dataset as an associated scientific workflow. This is integrated with linked-data compliant data re-use standards (e.g. OAI-ORE) to enable a seamless link between a publication and the complete trail of lineage of the corresponding dataset, including the dataset itself.

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Scholarly researchers today are increasingly required to engage in a range of data management planning activities to comply with institutional policies, or as a precondition for publication or grant funding. The latter is especially true in the U.S. in light of the recent White House Office of Science and Technology Policy (OSTP) mandate aimed at maximizing the availability of all outputs—data as well as the publications that summarize them—resulting from federally-funded research projects.

To aid researchers in creating effective data management plans (DMPs), a group of organizations—California Digital Library, DataONE, Digital Curation Centre, Smithsonian Institution, University of Illinois Urbana-Champaign, and University of Virginia Library—collaborated on the development of the DMPTool, an online application that helps researchers create data management plans. The DMPTool provides detailed guidance, links to general and institutional resources, and walks a researcher through the process of generating a comprehensive plan tailored to specific DMP requirements. The uptake of the DMPTool has been positive: to date, it has been used by over 6,000 researchers from 800 institutions, making use of more than 20 requirements templates customized for funding bodies.

With support from the Alfred P. Sloan Foundation, project partners are now engaged in enhancing the features of the DMPTool. The second version of the tool has enhanced functionality for plan creators and institutional administrators, as well as a redesigned user interface and an open RESTful application programming interface (API).

New administrative functions provide the means for institutions to better support local research activities. New capabilities include support for plan co-ownership; workflow provisions for internal plan review; simplified maintenance and addition of DMP requirements templates; extensive capabilities for the customization of guidance and resources by local institutional administrators; options for plan visibility; and UI refinements based on user feedback and focus group testing. The technical work undertaken for the DMPTool Version 2 has been accompanied by a new governance structure and the growth of a community of engaged stakeholders who will form the basis for a sustainable path forward for the DMPTool as it continues to play an important role in research data management activities.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Surkis, Alisa, Aileen McCrillis, Richard McGowan, Jeffrey Williams, Brian L. Schmidt, Markus Hardt, and Neil Rambo. "Informationist Support for a Study of the Role of Proteases and Peptides in Cancer Pain." Journal of eScience Librarianship 2, no. 1 (2013): 35-40.

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Scientific research in the 21st century is more data intensive and collaborative than in the past. It is important to study the data practices of researchers—data accessibility, discovery, re-use, preservation and, particularly, data sharing. Data sharing is a valuable part of the scientific method allowing for verification of results and extending research from prior results.

Methodology/Principal Findings

A total of 1329 scientists participated in this survey exploring current data sharing practices and perceptions of the barriers and enablers of data sharing. Scientists do not make their data electronically available to others for various reasons, including insufficient time and lack of funding. Most respondents are satisfied with their current processes for the initial and short-term parts of the data or research lifecycle (collecting their research data; searching for, describing or cataloging, analyzing, and short-term storage of their data) but are not satisfied with long-term data preservation. Many organizations do not provide support to their researchers for data management both in the short- and long-term. If certain conditions are met (such as formal citation and sharing reprints) respondents agree they are willing to share their data. There are also significant differences and approaches in data management practices based on primary funding agency, subject discipline, age, work focus, and world region.


Barriers to effective data sharing and preservation are deeply rooted in the practices and culture of the research process as well as the researchers themselves. New mandates for data management plans from NSF and other federal agencies and world-wide attention to the need to share and preserve data could lead to changes. Large scale programs, such as the NSF-sponsored DataNET (including projects like DataONE) will both bring attention and resources to the issue and make it easier for scientists to apply sound data management principles.

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The Oxford Dictionary defines provenance as "the place of origin, or earliest known history of something." The term, when transferred to its digital counterpart, has morphed into a more general meaning. It is not only used to refer to the origin of a digital artefact but also to its changes over time. By changes in this context we may not only refer to its digital snapshots but also to the processes that caused and materialised the change. As an example, consider a database record r created at point in time t0; an update u to that record at time t1 causes it to have a value r'. In terms of provenance, we do not only want to record the snapshots (t0, r) and (t1, r') but also the transformation u that when applied to (t0, r) results in (t1, r'), that is u(t0, r) = (t1, r').

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Vlaeminck, Sven. "Data Management in Scholarly Journals and Possible Roles for Libraries—Some Insights from EDaWaX." LIBER Quarterly 23, no. 1 (2013): 48-79.

In this paper we summarize the findings of an empirical study conducted by the EDaWaX-Project. 141 economics journals were examined regarding the quality and extent of data availability policies that should support replications of published empirical results in economics. This paper suggests criteria for such policies that aim to facilitate replications. These criteria were also used for analysing the data availability policies we found in our sample and to identify best practices for data policies of scholarly journals in economics. In addition, we also evaluated the journals' data archives and checked the percentage of articles associated with research data. To conclude, an appraisal as to how scientific libraries might support the linkage of publications to underlying research data in cooperation with researchers, editors, publishers and data centres is presented.

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Vlaeminck, Sven, and Gert G. Wagner. "On the Role of Research Data Centres in the Management of Publication-Related Research Data " LIBER Quarterly 23, no. 4 (2014): 336-357.

This paper summarizes the findings of an analysis of scientific infrastructure service providers (mainly from Germany but also from other European countries). These service providers are evaluated with regard to their potential services for the management of publication-related research data in the field of social sciences, especially economics. For this purpose we conducted both desk research and an online survey of 46 research data centres (RDCs), library networks and public archives; almost 48% responded to our survey. We find that almost three-quarters of all respondents generally store externally generated research data—which also applies to publication-related data. Almost 75% of all respondents also store and host the code of computation or the syntax of statistical analyses. If self-compiled software components are used to generate research outputs, only 40% of all respondents accept these software components for storing and hosting. Eight out of ten institutions also take specific action to ensure long-term data preservation. With regard to the documentation of stored and hosted research data, almost 70% of respondents claim to use the metadata schema of the Data Documentation Initiative (DDI); Dublin Core is used by 30 percent (multiple answers were permitted). Almost two-thirds also use persistent identifiers to facilitate citation of these datasets. Three in four also support researchers in creating metadata for their data. Application programming interfaces (APIs) for uploading or searching datasets currently are not yet implemented by any of the respondents. Least common is the use of semantic technologies like RDF.

Concluding, the paper discusses the outcome of our survey in relation to Research Data Centres (RDCs) and the roles and responsibilities of publication-related data archives for journals in the fields of social sciences.

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Waddington, Simon, Jun Zhang, Gareth Knight, Mark Hedges, Jens Jensen, and Roger Downing. "Kindura: Repository Services for Researchers Based on Hybrid Clouds " Journal of Digital Information 13, no. 1 (2012).

Walling, David, and Maria Esteva. "Automating the Extraction of Metadata from Archaeological Data Using iRods Rules." International Journal of Digital Curation 6, no. 2 (2011): 253-264.

Wallis, Jillian. "Data Producers Courting Data Reusers: Two Cases from Modeling Communities." International Journal of Digital Curation 9, no. 1 (2014): 98-109.

Data sharing is a difficult process for both the data producer and the data reuser. Both parties are faced with more disincentives than incentives. Data producers need to sink time and resources into adding metadata for data to be findable and usable, and there is no promise of receiving credit for this effort. Making data available also leaves data producers vulnerable to being scooped or data misuse. Data reusers also need to sink time and resources into evaluating data and trying to understand them, making collecting their own data a more attractive option. In spite of these difficulties, some data producers are looking for new ways to make data sharing and reuse a more viable option. This paper presents two cases from the surface and climate modeling communities, where researchers who produce data are reaching out to other researchers who would be interested in reusing the data. These cases are evaluated as a strategy to identify ways to overcome the challenges typically experienced by both data producers and data reusers. By working together with reusers, data producers are able to mitigate the disincentives and create incentives for sharing data. By working with data producers, data reusers are able to circumvent the hurdles that make data reuse so challenging.

This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License.

Wallis, Jillian C., Christine L. Borgman, Matthew S. Mayernik, and Alberto Pepe. "Moving Archival Practices Upstream: An Exploration of the Life Cycle of Ecological Sensing Data in Collaborative Field Research." International Journal of Digital Curation 3, no. 1 (2008): 114-126.

Wallis, Jillian C., Elizabeth Rolando, and Christine L. Borgman. "If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology." PLOS ONE 8, no. 7 (2013): e67332.

Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.

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Walton, David, Roy Lowry, and Sarah Callaghan. "Data Citation and Publication by NERC's Environmental Data Centres." Ariadne, no. 68 (2012).

Ward, Catharine, Lesley Freiman, Sarah Jones, Laura Molloy, and Kellie Snow. "Making Sense: Talking Data Management with Researchers." International Journal of Digital Curation 6, no. 2 (2011): 265-273.

Weber, Nicholas M., Carole L. Palmer, and Tiffany C. Chao. "Current Trends and Future Directions in Data Curation Research and Education." Journal of Web Librarianship 6, no. 4 (2012): 305-320.

Weber, Nicholas M., Andrea K. Thomer, Matthew S. Mayernik, Bob Dattore, Zaihua Ji, and Steve Worley. "The Product and System Specificities of Measuring Curation Impact." International Journal of Digital Curation 8, no. 2 (2013): 223-234.

Using three datasets archived at the National Center for Atmospheric Research (NCAR), we describe the creation of a 'data usage index' for curation-specific impact assessments. Our work is focused on quantitatively evaluating climate and weather data used in earth and space science research, but we also discuss the application of this approach to other research data contexts. We conclude with some proposed future directions for metric-based work in data curation.

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Wessels, Bridgette, Rachel L. Finn, Peter Linde, Paolo Mazzetti, Stefano Nativi, Susan Riley, Rod Smallwood, Mark J. Taylor, Victoria Tsoukala, Kush Wadhwa, and Sally Wyatt. "Issues in the Development of Open Access to Research Data." Prometheus: Critical Studies in Innovation 32, no. 1 (2014): 49-66.

Westra, Brian, Marisa Ramirez, Susan Wells Parham, and Jeanine Marie Scaramozzino. "Science and Technology Resources on the Internet: Selected Internet Resources on Digital Research Data Curation." Issues in Science and Technology Librarianship, no. 63 (2010).

White, Hollie C. "Considering Personal Organization: Metadata Practices of Scientists." Journal of Library Metadata 10, no. 2/3 (2010): 156-172.

———. "Descriptive Metadata for Scientific Data Repositories: A Comparison of Information Scientist and Scientist Organizing Behaviors." Journal of Library Metadata 14, no. 1 (2014): 24-51.

White, Wendy, Dorothy Byatt, and Steve Hitchcock. DataPool: Final Report Southampton, UK: University of Southampton, 2013.

Whyte, Angus, Dominic Job, Stephen Giles, and Stephen Lawrie. "Meeting Curation Challenges in a Neuroimaging Group." International Journal of Digital Curation 3, no. 1 (2008): 171-181.

Whyte, Angus, and Graham Pryor. "Open Science in Practice: Researcher Perspectives and Participation." International Journal of Digital Curation 6, no. 1 (2011): 199-213.

Wiley, Christie. "Metadata Use in Research Data Management." Bulletin of the American Society for Information Science and Technology 40, no. 6 (2014): 38-40.

Williams, Sarah C. "Data Practices in the Crop Sciences: A Review of Selected Faculty Publications." Journal of Agricultural & Food Information 13, no. 4 (2012): 308-325.

———. "Data Sharing Interviews with Crop Sciences Faculty: Why They Share Data and How the Library Can Help." Issues in Science and Technology Librarianship, no. 72 (2013).

———. "Gathering Feedback from Early-Career Faculty: Speaking with and Surveying Agricultural Faculty Members about Research Data." Journal of eScience Librarianship 2, no. 2 (2013).

———. "Using a Bibliographic Study to Identify Faculty Candidates for Data Services." Science & Technology Libraries 32, no. 2 (2013): 202-209.

Willis, Craig, Jane Greenberg, and Hollie White. "Analysis and Synthesis of Metadata Goals for Scientific Data." Journal of the American Society for Information Science and Technology 63, no. 8 (2012): 1505-1520.

Wilson, Andrew. "How Much Is Enough: Metadata for Preserving Digital Data." Journal of Library Metadata 10, no. 2/3 (2010): 205-217.

Wilson, James A. J., Michael A. Fraser, Luis Martinez-Uribe, Paul Jeffreys, Meriel Patrick, Asif Akram, and Tahir Mansoori. "Developing Infrastructure for Research Data Management at the University of Oxford." Ariadne, no. 65 (2010).

Wilson, James A. J., and Paul Jeffreys. "Towards a Unified University Infrastructure: The Data Management Roll-Out at the University of Oxford." International Journal of Digital Curation 8, no. 2 (2013): 235-246.

Since presenting a paper at the International Digital Curation Conference 2010 conference entitled 'An Institutional Approach to Developing Research Data Management Infrastructure', the University of Oxford has come a long way in developing research data management (RDM) policy, tools and training to address the various phases of the research data lifecycle. Work has now begun on integrating these various elements into a unified infrastructure for the whole university, under the aegis of the Data Management Roll-out at Oxford (Damaro) Project.

This paper will explain the process and motivation behind the project, and describes our vision for the future. It will also introduce the new tools and processes created by the university to tie the individual RDM components together. Chief among these is the 'DataFinder'—a hierarchically-structured metadata cataloguing system which will enable researchers to search for and locate research datasets hosted in a variety of different datastores from institutional repositories, through Web 2 services, to filing cabinets standing in department offices. DataFinder will be able to pull and associate research metadata from research information databases and data management plans, and is intended to be CERIF compatible. DataFinder is being designed so that it can be deployed at different levels within different contexts, with higher-level instances harvesting information from lower-level instances enabling, for example, an academic department to deploy one instance of DataFinder, which can then be harvested by another at an institutional level, which can then in turn be harvested by another at a national level.

The paper will also consider the requirements of embedding tools and training within an institution and address the difficulties of ensuring the sustainability of an RDM infrastructure at a time when funding for such endeavours is limited. Our research shows that researchers (and indeed departments) are at present not exposed to the true costs of their (often suboptimal) data management solutions, whereas when data management services are centrally provided the full costs are visible and off-putting. There is, therefore, the need to sell the benefits of centrally-provided infrastructure to researchers. Furthermore, there is a distinction between training and services that can be most effectively provided at the institutional level, and those which need to be provided at the divisional or departmental level in order to be relevant and applicable to researchers. This is being addressed in principle by Oxford's research data management policy, and in practice by the planning and piloting aspects of the Damaro Project.

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Wilson, James A. J., Luis Martinez-Uribe, Michael A. Fraser, and Paul Jeffreys. "An Institutional Approach to Developing Research Data Management Infrastructure." International Journal of Digital Curation 6, no. 2 (2011): 274-287.

Witt, Michael. "Co-designing, Co-developing, and Co-implementing an Institutional Data Repository Service." Journal of Library Administration 52, no. 2 (2012): 172-188.

———. "Institutional Repositories and Research Data Curation in a Distributed Environment." Library Trends 57, no. 2 (2008): 191-201.

Wright, Sarah J., Wendy A. Kozlowski, Dianne Dietrich, Huda J. Khan, and Gail S. Steinhart. "Using Data Curation Profiles to Design the Datastar Dataset Registry." D-Lib Magazine 19, no. 7/8 (2013).

Wright, Stephanie, Amanda Whitmire, Lisa Zilinski, and David Minor. "Collaboration and Tension between Institutions and Units Providing Data Management Support." Bulletin of the American Society for Information Science and Technology 40, no. 6 (2014): 18-21.

Woolfrey, H. "Innovations for the Curation and Sharing of African Social Survey Data." Data Science Journal 12 (2013): WDS185-WDS188.

A substantial amount of data is collected through surveys conducted in Africa by national statistics offices, international donor organisations, research institutions, and the private sector. Data management at African national statistics offices is hampered by limited resources. An option for data curation in African countries is the establishment of dedicated institutions for data preservation and dissemination, such as survey data archives, and research data centres. DataFirst, at the University of Cape Town, has established an African data service and is helping to improve African data curation practices through providing data, promoting free curation tools, and undertaking data management training in African countries.

This work is licensed under a Creative Commons Attribution 3.0 License.

Wynholds, Laura. "Linking to Scientific Data: Identity Problems of Unruly and Poorly Bounded Digital Objects." International Journal of Digital Curation 6, no. 1 (2011): 214-225.

Xia, Jingfeng. "Mandates and the Contributions of Open Genomic Data." Publications 1, no. 3 (2013): 99-112.

Yang, Yanyan, Omer F. Rana, David W. Walker, Roy Williams, Christos Georgousopoulos, Massimo Caffaro, and Giovanni Aloisio. "An Agent Infrastructure for On-Demand Processing of Remote-Sensing Archives." International Journal on Digital Libraries 5, no. 2 (2005): 120-132.

Yoon, Ayoung. "End Users' Trust in Data Repositories: Definition and Influences on Trust Development." Archival Science 14, no. 1 (2014): 17-34.

Yoon, Ayoung, and Helen Tibbo. "Examination of Data Deposit Practices in Repositories with the OAIS Model." IASSIST Quarterly 35, no. 4 (2011): 6-13.

Zborowski, Mary. "Data Management Activities of Canada's National Science Library—2010 Update and Prospective." Data Science Journal 9 (2011): 100-106.

NRC-CISTI serves Canada as its National Science Library (as mandated by Canada's Parliament in 1924) and also provides direct support to researchers of the National Research Council of Canada (NRC). By reason of its mandate, vision, and strategic positioning, NRC-CISTI has been rapidly and effectively mobilizing Canadian stakeholders and resources to become a lead player on both the Canadian national and international scenes in matters relating to the organization and management of scientific research data. In a previous communication (CODATA International Conference, 2008), the orientation of NRC-CISTI towards this objective and its short- and medium-term plans and strategies were presented. Since then, significant milestones have been achieved. This paper presents NRC-CISTI's most recent activities in these areas, which are progressing well alongside a strategic organizational redesign process that is realigning NRC-CISTI's structure, mission, and mandate to better serve its clients. Throughout this transformational phase, activities relating to data management remain vibrant.

This work is licensed under a Creative Commons Attribution 3.0 License.

Zenk-Möltgen, Wolfgang, and Greta Lepthien. "Data Sharing in Sociology Journals." Online Information Review 38, no. 6 (2014): 709-722.

Zimmerman, Ann. "Not by Metadata Alone: The Use of Diverse Forms of Knowledge to Locate Data for Reuse." International Journal on Digital Libraries 7, no. 1/2 (2007): 5-16.

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Related Bibliographies and Webliographies

Bailey, Charles W., Jr. Digital Curation and Preservation Bibliography 2010. Houston: Digital Scholarship, 2011.

———. Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works. Houston: Digital Scholarship, 2012.

———. Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works, 2012 Supplement Houston: Digital Scholarship, 2013.

———. Digital Curation Resource Guide Houston: Digital Scholarship, 2012.

About the Author

Charles W. Bailey, Jr. is a digital artist and the publisher of Digital Scholarship.

Bailey transforms photographs into digital artworks using specialized Photoshop plug-ins and art programs, such as Alien Skin Snap Art 4 and Topaz Impression. He primarily creates digital oil and impasto paintings and charcoal, oil pastel, and pastel drawings. He has made over 300 digital artworks available on Flickr and other social media sites, providing detailed information about how each artwork was created. They have been viewed over 900,000 times on Google+ alone.

Bailey has over 30 years of information and instructional technology experience, including 24 years of managerial experience in academic libraries. From 2004 to 2007, he was the Assistant Dean for Digital Library Planning and Development at the University of Houston Libraries. From 1987 to 2003, he served as Assistant Dean/Director for Systems at the University of Houston Libraries.

Previously, he served as Head, Systems and Research Services at the Health Sciences Library, The University of North Carolina at Chapel Hill; Systems Librarian at the Milton S. Eisenhower Library, The Johns Hopkins University; User Documentation Specialist at the OCLC Online Computer Library Center; and Media Library Manager at the Learning Resources Center, SUNY College at Oswego. See Bailey's vita for more details.

Bailey has been an open access publisher for over 25 years. In 1989, Bailey established PACS-L, a discussion list about public-access computers in libraries, and The Public-Access Computer Systems Review, the first open access journal in the field of library and information science. He served as PACS-L Moderator until November 1991 and as Editor-in-Chief of The Public-Access Computer Systems Review until the end of 1996.

In 1990, Bailey and Dana Rooks established Public-Access Computer Systems News, an electronic newsletter, and Bailey co-edited this publication until 1992.

In 1992, he founded the PACS-P mailing list for announcing the publication of selected e-serials, and he moderated this list until 2007.

In 1996, he established the Scholarly Electronic Publishing Bibliography (SEPB), an open access book that was updated 80 times.

In 2001, he added the Scholarly Electronic Publishing Weblog, which announces relevant new publications, to SEPB.

In 2001, he was selected as a team member of Current Cites, and he has subsequently been a frequent contributor of reviews to this monthly e-serial.

In 2005, he published the Open Access Bibliography: Liberating Scholarly Literature with E-prints and Open Access Journals with the Association of Research Libraries (also a website).

In 2005, Bailey established Digital Scholarship (, which provides information and commentary about digital copyright, digital curation, digital repository, open access, scholarly communication, and other digital information issues. Digital Scholarship's digital publications are open access. Its publications are under versions of the Creative Commons Attribution-Noncommercial License.

At that time, he also established DigitalKoans, a weblog that covers the same topics as Digital Scholarship.

From April 2005 through March 2015, Digital Scholarship had over 14.9 million visitors from 231 counties, over 72 million file requests, and over 52 million page views. Excluding spiders, there were over 9 million visitors from 231 counties, over 43.4 million file requests, and over 24.1 million page views.

During this period, Bailey published the following books and book supplements: the Scholarly Electronic Publishing Bibliography: 2008 Annual Edition (2009), Digital Scholarship 2009 (2010), Transforming Scholarly Publishing through Open Access: A Bibliography (2010), the Scholarly Electronic Publishing Bibliography 2010 (2011), the Digital Curation and Preservation Bibliography 2010 (2011), the Institutional Repository and ETD Bibliography 2011 (2011), the Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works (2012), and the Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works, 2012 Supplement (2013).

He also published and updated the following bibliographies and webliographies as websites with links to freely available works: the Scholarly Electronic Publishing Bibliography (1996-2011), the Electronic Theses and Dissertations Bibliography (2005-2012), the Google Books Bibliography (2005-2011), the Institutional Repository Bibliography (2009-2011), the Open Access Journals Bibliography (2010), the Digital Curation and Preservation Bibliography (2010-2011), the E-science and Academic Libraries Bibliography (2011), the Digital Curation Resource Guide (2012), the Research Data Curation Bibliography (2012-2014),the Altmetrics Bibliography (2013), and the Transforming Peer Review Bibliography (2014).

In 2011, he established the LinkedIn Digital Curation Group.

For more details, see the "Digital Scholarship Publications Overview."

In 2010, Bailey was given a Best Content by an Individual Award by The Charleston Advisor. In 2003, he was named as one of Library Journal's "Movers & Shakers." In 1993, he was awarded the first LITA/Library Hi Tech Award For Outstanding Communication for Continuing Education in Library and Information Science.

In 1973, Bailey won a Wallace Stevens Poetry Award. He is the author of The Cave of Hypnos: Early Poems, which includes several poems that won that award.

Bailey has written over 30 papers about digital copyright, expert systems, institutional repositories, open access, scholarly communication, and other topics.

He has served on the editorial boards of Information Technology and Libraries, Library Software Review, and Reference Services Review.

He holds master's degrees in information and library science and instructional media and technology.

You can follow Bailey at these URLs:

His e-mail address is cb at