Data Curation, Open Data, and Research Data Management – Page 44

"Developing Professional Skills in STEM Students: Data Information Literacy"

Lisa D. Zilinski et al. have published "Developing Professional Skills in STEM Students: Data Information Literacy" in Issues in Science and Technology Librarianship.

Here's an excerpt:

Undergraduate STEM students are increasingly expected to have some data use skills upon graduation, whether they pursue post-graduate education or move into industry. This project was an initial foray into the application of data information literacy competencies to training undergraduate students to identify markers of data and information quality. The data consumer training appeared within two courses to help students evaluate data objects, including databases and datasets available on the Internet. The application of the Data Credibility Checklist provides a foundation for developing data reuse competencies. Based upon the initial presentation of the content, it became obvious that students need very basic introductions to data concepts, including definitions for database and dataset, and the process of data object discovery.

Digital Scholarship | "A Quarter-Century as an Open Access Publisher"

"Library of Congress Recommended Format Specifications: Encouraging Preservation Without Discouraging Creation"

Theron Westervelt has published "Library of Congress Recommended Format Specifications: Encouraging Preservation Without Discouraging Creation" in D-Lib Magazine.

Here's an excerpt:

The Library of Congress has a fundamental commitment to acquiring, preserving and making accessible in the long term the creative output of the nation and the world. The Library has devised the Recommended Format Specifications to enable it to identify what formats will most easily lend themselves to preservation and long-term access, especially with regard to digital formats. The Library has done this to provide guidance to its staff in their work of acquiring content for its collection, but also seeks to share this with other stakeholders, from the creative community to vendors to other libraries, each of which has a need and interest in preservation and access. To ensure ongoing accuracy and relevancy, the Library of Congress will be reviewing and revising the specifications on an annual basis and welcomes feedback and input from all interested parties.

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"How Many Citations Are There in the Data Citation Index?"

Daniel Torres-Salinas et al. have self-archived "How Many Citations Are There in the Data Citation Index?."

Here's an excerpt:

Descriptive analysis on the citation distribution of the Thomson Reuters' Data Citation Index by publication type and four broad areas: Science, Engineering & Technology, Humanities & Arts and Social Sciences.

Digital Scholarship | "A Quarter-Century as an Open Access Publisher"

Current Quality Assurance Practices in Web Archiving

Brenda Reyes Ayala, Mark E. Phillips, and Lauren Ko have self-archived Current Quality Assurance Practices in Web Archiving.

Here's an excerpt:

This paper presents the results of a survey of quality assurance (QA) practices within the field of web archiving. To understand current QA practices, the authors surveyed 54 institutions engaged in web archiving, which included national libraries, colleges and universities, and museums and art libraries.

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"Going Beyond Data Management Planning: Comprehensive Research Data Services"

Katherine G. Akers has published "Going Beyond Data Management Planning: Comprehensive Research Data Services" in College & Research Libraries News.

Here's an excerpt:

We should keep in mind that DMP requirements impact only a small proportion of academic researchers and, furthermore, that such requirements are only one factor motivating researchers to share their data. Just as many, if not a greater number of, researchers might face expectations from journal publishers to share the data underlying their research articles. Some researchers receive funding from federal agencies that have data sharing policies but that do not require a DMP. Also, many researchers may desire to make their data available to a wide audience for personal or altruistic reasons, such as to permit others to replicate their methods and analysis, to allow others to re-purpose their data in new ways, or to increase the visibility and impact of their work.

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"Steal This Idea: A Library Instructors’ Guide to Educating Students in Data Management Skills"

Lisa Johnston and Jon Jeffryes have published "Steal This Idea: A Library Instructors' Guide to Educating Students in Data Management Skills" in College & Research Libraries News.

Here's an excerpt:

This article provides a big-picture overview of the work conducted by UM to meet the data literacy needs of our graduate students. We've adapted our instructional approach to data management over the years.

Digital Scholarship | "A Quarter-Century as an Open Access Publisher"

"Integrating Approaches to Privacy Across the Research Lifecycle: Long-Term Longitudinal Studies"

Alexandra Wood et al. have self-archived "Integrating Approaches to Privacy Across the Research Lifecycle: Long-Term Longitudinal Studies."

Here's an excerpt:

The defining characteristics of a long-term longitudinal study—that such a study follows a large number of individuals over extended periods of time and collects vast quantities of sometimes very sensitive personal information from subjects—create a number of challenges for researchers working with longitudinal data. Over the course of a longitudinal study, data collection, uses of data, privacy expectations, and laws may change, leaving the scope of subjects' consent unclear. The use of contractors for data collection and the need to retain administrative data linked to records to recontact subjects over time may increase the risk of disclosure.

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"Dealing with Data: Science Librarians’ Participation in Data Management at Association of Research Libraries Institutions"

Karen Antell et al. have published "Dealing with Data: Science Librarians' Participation in Data Management at Association of Research Libraries Institutions" in College & Research Libraries.

Here's an excerpt:

This study, a survey of science librarians at institutions affiliated with the Association of Research Libraries, investigates science librarians' awareness of and involvement in institutional repositories, data repositories, and data management support services at their institutions. The study also explores the roles and responsibilities, both new and traditional, that science librarians have assumed related to data management, and the skills that science librarians believe are necessary to meet the demands of data management work.

Digital Scholarship | Research Data Curation Bibliography, Version 4

"Research Data Management Case Studies"

LIBER's Steering Committee on Scholarly Communication and Research Infrastructures has released "Research Data Management Case Studies."

Here's an excerpt from the announcement:

These studies describe policies and strategies that pave the way for the creation, institutional integration and the running of support services and underlying infrastructures. In addition, challenges and lessons learned are described, and ways-forward outlined.

Digital Scholarship | Research Data Curation Bibliography, Version 4

Preserving eBooks

The Digital Preservation Coalition has released Preserving eBooks.

Here's an excerpt from the announcement:

Written by Portico's Amy Kirchhoff and Sheila Morrissey, and published in association with Charles Beagrie Ltd., this report discusses the current developments and issues with which public, national and higher education libraries, publishers, aggregators and preservation institutions must contend to ensure long-term access to eBook content.

Digital Scholarship | "A Quarter-Century as an Open Access Publisher"

Research Data Curation Bibliography, Version 4

Digital Scholarship has released version 4 of the Research Data Curation Bibliography. This selective bibliography includes over 320 English-language articles and technical reports that are useful in understanding the curation of digital research data in academic and other research institutions.

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.

Most sources have been published from January 2009 through June 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.

It is available under a Creative Commons Attribution-Noncommercial 3.0 United States License.

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.

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"The ‘Digital’ Scholarship Disconnect"

Clifford Lynch has published "The 'Digital' Scholarship Disconnect" in EDUCAUSE Review.

Here's an excerpt:

Still, in all of these examples of digital scholarship, a key challenge remains: How can we curate and manage data now that so much of it is being produced and collected in digital form? How can we ensure that it will be discovered, shared, and reused to advance scholarship? We are struggling through the establishment of institutions, funding models, policies and practices, and even new legal requirements and community norms—ranging from cultural changes about who can use data (and when) to economic decisions about who should pay for what. Some disciplines are less contentious than others: for example, astronomy data is technically well-understood and usually not terribly sensitive. Reputation, rather than commercial reward, is wrapped up in astronomical discoveries, and there is no institutional review board to ensure the safety and dignity of astronomical objects. On the other hand, human subjects and their data raise an enormous number of questions about informed consent, privacy, and anonymization; when there are genetic markers or possible treatments to be discovered or validated, serious high-value commercial interests may be at stake. All of these factors tend to work against the free and convenient sharing of data.

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"The University Library as Incubator for Digital Scholarship"

Bryan Sinclair has published "The University Library as Incubator for Digital Scholarship" in EDUCAUSE Review.

Here's an excerpt:

The campus of the future will be increasingly connected and collaborative, and the library can be the community center and beta test kitchen for new forms of interdisciplinary inquiry. Libraries have always been in the business of knowledge creation and transfer, and the digital scholarship incubator within the library can serve as a natural extension of this essential function. In an age of visualization, analytics, big data, and new forms of online publishing, these central spaces can facilitate knowledge creation and transfer by connecting people, data, and technology in a shared collaborative space.

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"Developing a Research Data Management Service—A Case Study"

Jeff Moon has published "Developing a Research Data Management Service—A Case Study" in Partnership.

Here's an excerpt:

Publicly-funded, researcher-generated data has been on the front burner lately, driven by a variety of factors, including evolving funding-agency policies and journal publisher requirements. In this context, Queen's University Library (QUL) developed and implemented a Research Data Management (RDM) Service to meet researchers' needs. This process is described here, framed around four main themes: planning, building, educating, and doing.

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"Research Data Sharing: Developing a Stakeholder-Driven Model for Journal Policies"

Paul Sturges et al. have self-archived "Research Data Sharing: Developing a Stakeholder-Driven Model for Journal Policies."

Here's an excerpt:

The Journal Research Data (JoRD) Project was a JISC (Joint Information Systems Committee) funded feasibility study on the possible shape of a central service on journal research data policies. The objectives of the study included, amongst other considerations: to identify the current state of journal data sharing policies and to investigate the views and practices of stakeholders to data sharing. The project confirmed that a large percentage of journals do not have a policy on data sharing, and that there are inconsistencies between the traceable journal data sharing policies. Such a state leaves authors unsure of whether they should deposit data relating to articles and where and how to share that data. In the absence of a consolidated infrastructure for the easy sharing of data, a journal data sharing model policy was developed. The model policy was developed from comparing the quantitative information gathered from analysing existing journal data policies with qualitative data collected from the stakeholders concerned. This article summarises the information gathered, outlines the process by which the model was developed and presents the model journal data sharing policy in full.

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"PLOS Data Policy: Catalyst for a Better Research Process"

Emma Ganley has published "PLOS Data Policy: Catalyst for a Better Research Process" in College & Research Libraries News.

Here's an excerpt:

PLOS is seeking to ensure the ongoing utility of research, as making a paper openly accessible is enhanced enormously if that paper is linked seamlessly to the data from which it was constructed. In a time when post-publication peer review is more prevalent and data frequently come under intense public scrutiny, with whistle-blowers, blogs, and websites dedicated to investigating the validity and veracity of scientific publications, requiring access to the relevant data leads to a more rigorous scientific record.

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"PyRDM: A Python-Based Library for Automating the Management and Online Publication of Scientific Software And Data"

Christian T. Jacobs et al. have self-archived "PyRDM: A Python-Based Library for Automating the Management and Online Publication of Scientific Software And Data."

Here's an excerpt:

The recomputability and reproducibility of results from scientific software requires access to both the source code and all associated input and output data. However, the full collection of these resources often does not accompany the key findings published in journal articles, thereby making it difficult or impossible for the wider scientific community to verify the correctness of a result or to build further research on it. This paper presents a new Python-based library, PyRDM, whose functionality aims to automate the process of sharing the software and data via online, citable repositories such as Figshare. The library is integrated into the workflow of an open-source computational fluid dynamics package, Fluidity, to demonstrate an example of its usage.

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"Peer Review of Datasets: When, Why, and How"

Matthew S. Mayernik et al. have published "Peer Review of Datasets: When, Why, and How" in the Bulletin of the American Meteorological Society.

Here's an excerpt:

This paper discusses issues related to data peer review, in particular the peer review processes, needs, and challenges related to the following scenarios: 1) Data analyzed in traditional scientific articles, 2) Data articles published in traditional scientific journals, 3) Data submitted to open access data repositories, and 4) Datasets published via articles in data journals.

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U.S. Open Data Action Plan

The White House has released the U.S. Open Data Action Plan.

Here's an excerpt:

The Smithsonian Cooper-Hewitt National Design Museum Collection plans to make all digitized collections metadata public domain, and digitized collection images without copyright or other restriction publicly available at the highest available resolution for non-commercial, educational use. . . .

The Smithsonian Freer Gallery of Art and Arthur M. Sackler Gallery plans to make all digitized collections metadata public domain, and digitized collection images without copyright or other restriction publicly available at the highest available resolution for non-commercial, educational use. . . .

After a successful limited release of an API of the Smithsonian American Art Museum collection and hackathon that resulted in a number of working prototypes, the Smithsonian American Art Museum is planning a staged release, from open metadata, like artist or medium, to an open API of digitized collections images without copyright or other restriction available for non- commercial, educational use.

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Big Data: Seizing Opportunities, Preserving Values

The Executive Office of the President has released Big Data: Seizing Opportunities, Preserving Values.

Here's an excerpt:

On January 17, in a speech at the Justice Department about reforming the United States' signals intelligence practices, President Obama tasked his Counselor John Podesta with leading a comprehensive review of the impact big data technologies are having, and will have, on a range of economic, social, and government activities. Podesta was joined in this effort by Secretary of Commerce Penny Pritzker, Secretary of Energy Ernest Moniz, the President's Science Advisor John Holdren, the President's Economic Advisor Jeffrey Zients, and other senior government officials. The President's Council of Advisors for Science & Technology conducted a parallel report to take measure of the underlying technologies. Their findings underpin many of the technological assertions in this report.

This review was conceived as fundamentally a scoping exercise. Over 90 days, the review group engaged with academic experts, industry representatives, privacy advocates, civil rights groups, law enforcement agents, and other government agencies. The White House Office of Science and Technology Policy jointly organized three university conferences, at the Massachusetts Institute of Technology, New York University, and the University of California, Berkeley. The White House Office of Science & Technology Policy also issued a "Request for Information" seeking public comment on issues of big data and privacy and received more than 70 responses. In addition, the WhiteHouse.gov platform was used to conduct an unscientific survey of public attitudes about different uses of big data and various big data technologies. A list of the working group's activities can be found in the Appendix.

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What Drives Academic Data Sharing?

RatSWD has released What Drives Academic Data Sharing?.

Here's an excerpt:

Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration.

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"Data Publication Consensus and Controversies"

F1000Research has released an eprint of "Data Publication Consensus and Controversies."

Here's an excerpt:

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.

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How to Discover Requirements for Research Data Management Services

The DCC and DataONE have released How to Discover Requirements for Research Data Management Services.

Here's an excerpt:

This guide is meant for people whose role involves developing services or tools to support research data management (RDM) and digital curation, whether in a Higher Education Institution or a project working across institutions. Your RDM development role might be embedded with the research groups concerned, or at a more centralised level, such as a library or computing service. You will need a methodical approach to plan, elicit, analyse, document and prioritise a range of users' requirements.

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The Value and Impact of Data Sharing and Curation: A Synthesis of Three Recent Studies of UK Research Data Centres

JISC has released The Value and Impact of Data Sharing and Curation: A Synthesis of Three Recent Studies of UK Research Data Centres.

Here's an excerpt from the announcement:

The data centre studies combined quantitative and qualitative approaches in order to quantify value in economic terms and present other, non-economic, impacts and benefits. Uniquely, the studies cover both users and depositors of data, and we believe the surveys of depositors undertaken are the first of their kind. All three studies show a similar pattern of findings, with data sharing via the data centres having a large measurable impact on research efficiency and on return on investment in the data and services. These findings are important for funders, both for making the economic case for investment in data curation and sharing and research data infrastructure, and for ensuring the sustainability of such research data centres.

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"Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets"

Christopher W. Belter has published "Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets" in PLOS ONE.

Here's an excerpt:

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.

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