Data Curation, Open Data, and Research Data Management – Page 7

"Data Journals: Where Data Sharing Policy Meets Practice"

Data journals incorporate elements of traditional scholarly communications practices—reviewing for quality and rigor through editorial and peer-review—and the data sharing / open data movement—prioritizing broad dissemination through repositories, sometimes with curation or technical checks. Their goals for dataset review and sharing are recorded in journal-based data policies and operationalized through workflows. In this qualitative, small cohort semi-structured interview study of eight different journals that review and publish research data, we explored (1) journal data policy requirements, (2) data review standards, and (3) implementation of standardized data evaluation workflows. Differences among the journals can be understood by considering editors’ approaches to balancing the interests of varied stakeholders. Assessing data quality for reusability is primarily conditional on fitness for use which points to an important distinction between disciplinary and discipline-agnostic data journals.

https://doi.org/10.17615/nqtz-b568

"Who Re-Uses Data? A Bibliometric Analysis of Dataset Citations"

Open data is receiving increased attention and support in academic environments, with one justification being that shared data may be re-used in further research. But what evidence exists for such re-use, and what is the relationship between the producers of shared datasets and researchers who use them? Using a sample of data citations from OpenAlex, this study investigates the relationship between creators and citers of datasets at the individual, institutional, and national levels. We find that the vast majority of datasets have no recorded citations, and that most cited datasets only have a single citation. Rates of self-citation by individuals and institutions tend towards the low end of previous findings and vary widely across disciplines. At the country level, the United States is by far the most prominent exporter of re-used datasets, while importation is more evenly distributed. Understanding where and how the sharing of data between researchers, institutions, and countries takes place is essential to developing open research practices.

https://arxiv.org/abs/2308.04379

"Metadata Standard for Continuous Preservation, Discovery, and Reuse of Research Data in Repositories by Higher Education Institutions: A Systematic Review"

This systematic review synthesised existing research papers that explore the available metadata standards to enable researchers to preserve, discover, and reuse research data in repositories. This review provides a broad overview of certain aspects that must be taken into consideration when creating and assessing metadata standards to enhance research data preservation discoverability and reusability strategies. Research papers on metadata standards, research data preservation, discovery and reuse, and repositories published between January 2003 and April 2023 were reviewed from a total of five databases. The review retrieved 1597 papers, and 13 papers were selected in this review. We revealed 13 research articles that explained the creation and application of metadata standards to enhance preservation, discovery, and reuse of research data in repositories. Among them, eight presented the three main types of metadata, descriptive, structural, and administrative, to enable the preservation of research data in data repositories. We noted limited evidence on how these metadata standards can be used to enhance the discovery and reuse of research data in repositories to enable the preservation, discovery, and reuse of research data in repositories. No reviews indicated specific higher education institutions employing metadata standards for the research data created by their researchers. Repository designs and a lack of expertise and technology know-how were among the challenges identified from the reviewed papers. The review has the potential to influence professional practice and decision-making by stakeholders, including researchers, students, librarians, information communication technologists, data managers, private and public organisations, intermediaries, research institutions, and non-profit organizations.

https://doi.org/10.3390/info14080427

"ARL Awarded Grant to Continue Research on Institutional Expenses for Public Access to Research Data"

The US Institute of Museum and Library Services (IMLS) has awarded the Association of Research Libraries (ARL), in collaboration with Duke University, the University of Minnesota, and Washington University in St. Louis, all of whom are members of the Data Curation Network (DCN), a $741,921 National Leadership Grant to examine institutional expenses for public access to research data. This research builds upon ARL’s existing Realities of Academic Data Sharing initiative.

https://tinyurl.com/378dzab6

"Association of Research Libraries and California Digital Library Receive Grant to Advance Data Management and Sharing"

The Association of Research Libraries (ARL) and the California Digital Library (CDL) have received a $668,048 National Leadership Grant from the US Institute of Museum and Library Services (IMLS) to assist institutions in managing and sharing federally funded research data. This project will build a machine-actionable data-management plan (maDMP) tool by enhancing and developing new DMPTool features utilizing persistent identifiers (PIDs). CDL and ARL will work together to further strengthen institutional capacity for tracking research outputs by piloting the institutional integration of maDMPs across an academic campus and building community across institutions for maDMPs.

https://tinyurl.com/35x9d45z

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

"New at Dryad: Support for NIH-funded researchers"

Dryad provides a simple submission process that makes it easy for researchers to upload your datasets, apply metadata that makes them discoverable and reusable, and get a persistent identifier (DOI) you can use in grant reporting. Once submitted, datasets are made publicly accessible so they can be reused by others in order to advance scientific discovery and collaboration across disciplines. Dryad also provides an extensive library of existing datasets from various sources, including those funded by NIH grants, that are completely free to access and reuse.

https://tinyurl.com/4uu9tz2r

"Data Sharing Implementation in Top 10 Ophthalmology Journals in 2021"

Background/Aims: Deidentified individual participant data (IPD) sharing has been implemented in the International Committee of Medical Journal Editors journals since 2017. However, there were some published clinical trials that did not follow the new implemented policy. This study examines the number of clinical trials that endorsed IPD sharing policy among top ophthalmology journals.

Method: All published original articles in 2021 in 10 highest-ranking ophthalmology journals according to the 2020 journal impact factor were included. Clinical trials were determined by the WHO definition of clinical trials. Each article was then thoroughly searched for the IPD sharing statement either in the manuscript or in the clinical trial registry. We collected the number of published clinical trials that implemented IPD sharing policy as our primary outcome.

Results: 1852 published articles in top 10 ophthalmology journals were identified, and 9.45% were clinical trials. Of these clinical trials, 44% had clinical trial registrations and 49.14% declared IPD sharing statements. Only 42 (48.83%) clinical trials were willing to share IPD, and 5 (10.21%) of these share IPD via an online repository platform. In terms of sharing period, 37 clinical trials were willing to share right after the publication and only 2 showed the ending of sharing period.

Conclusion: This report shows that the number of clinical trials in top ophthalmology journals that endorsed the IPD sharing policy and the number of registrations is lower than half even though the policy has been implemented for several years. Future updates are necessary as policy evolves.

http://dx.doi.org/10.1136/bmjophth-2023-001276

"eLife and PREreview to Enhance the ‘Publish, Review, Curate’ Ecosystem Through Adoption of COAR Notify"

The project will put in place the basic infrastructure and protocols needed for all-round and standardised connections between preprint repositories, community-led preprint review platforms, journals, and preprint review aggregation and curation platforms. The aim is to lower existing technological and cost barriers so that as many of these services as possible can more easily participate in the ‘publish, review, curate’ future for research.

https://tinyurl.com/36emyk9b

"Springer Nature Continues Open Research Drive with Acquisition of protocols.io"

Scientific advancement depends on data credibility and work that can be verified, built upon and reproduced. Sharing all elements of research, including data, methods and materials, and even negative results, makes research more efficient, enables reproducibility and therefore builds trust in science. Studies show that lack of awareness of existing work or negative results leads to unnecessary duplication and could waste up to €26 billion in Europe alone.

By laying out detailed step-by-step instructions for research methods, aiming to standardise the process, ensure accuracy of results and enabling research to be reproduced, protocols have a vital role to play in addressing this. With protocols.io joining Springer Nature’s leading protocol offering, researchers will now have the option to make their protocols openly available on the protocols.io platform (fully OA) as well as publishing them in peer-reviewed publications (searchable via the Springer Nature Experiments).

https://tinyurl.com/3j4kn49w

"Trends in Research Data Management and Academic Health Sciences Libraries"

Spurred by the National Institute of Health mandating a data management and sharing plan as a requirement of grant funding, research data management has exploded in importance for librarians supporting researchers and research institutions. This editorial examines the role and direction of libraries in this process from several viewpoints. Key markers of success include collaboration, establishing new relationships, leveraging existing relationships, accessing multiple avenues of communication, and building niche expertise and cachè as a valued and trustworthy partner. [Article includes case studies.]

https://doi.org/10.1080/02763869.2023.2218776

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

SPARC: "Oppose Section 552 That Will Block Taxpayer Access to Research"

The U.S. House Appropriations Subcommittee on Commerce, Justice, and Science (CJS) has released an appropriations bill containing language that would block implementation of the 2022 updated OSTP policy guidance (the Nelson Memo) that would ensure immediate, free access to taxpayer-funded research. If enacted, this will prevent American taxpayers from seeing the benefits of the more than $90 billion in scientific research that the U.S. government funds each year. . . .

Write to Congress

Look up contact details for your Representatives and Senators, then customize the text in this template letter.

Call Congress

Look up contact details for your Representatives and Senators, then call the office and tell them to remove Section 552 of the House CJS bill.

https://tinyurl.com/3mbbmwxw

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

"How Are Exclusively Data Journals Indexed in Major Scholarly Databases? An Examination of the Web of Science, Scopus, Dimensions, and OpenAlex"

As part of the data-driven paradigm and open science movement, the data paper is becoming a popular way for researchers to publish their research data, based on academic norms that cross knowledge domains. Data journals have also been created to host this new academic genre. The growing number of data papers and journals has made them an important large-scale data source for understanding how research data is published and reused in our research system. One barrier to this research agenda is a lack of knowledge as to how data journals and their publications are indexed in the scholarly databases used for quantitative analysis. To address this gap, this study examines how a list of 18 exclusively data journals (i.e., journals that primarily accept data papers) are indexed in four popular scholarly databases: the Web of Science, Scopus, Dimensions, and OpenAlex. We investigate how comprehensively these databases cover the selected data journals and, in particular, how they present the document type information of data papers. We find that the coverage of data papers, as well as their document type information, is highly inconsistent across databases, which creates major challenges for future efforts to study them quantitatively. As a result, we argue that efforts should be made by data journals and databases to improve the quality of metadata for this emerging genre.

https://arxiv.org/abs/2307.09704

"Prevalence and Predictors of Data and Code Sharing in the Medical and Health Sciences: Systematic Review with Meta-Analysis of Individual Participant Data"

The review found that public code sharing was persistently low across medical research. Declarations of data sharing were also low, increasing over time, but did not always correspond to actual sharing of data. The effectiveness of mandatory data sharing policies varied substantially by journal and type of data, a finding that might be informative for policy makers when designing policies and allocating resources to audit compliance.

https://doi.org/10.1136/bmj-2023-075767

Directions in Digital Scholarship: Support for Digital, Data-Intensive, and Computational Research in Academic Libraries

This report of a 2023 Coalition for Networked Information (CNI) initiative takes a broad look at library engagement with digital scholarship (DS) and examines connections with data-intensive and computational research over roughly the past five years and into the future. . . . To understand trends in DS programs, including attention to the impact of the pandemic, especially with reference to the importance of physical spaces and in-person programming, evidence was gathered from several sources, including online interviews with 12 library and DS leaders, profiles of 47 libraries’ DS programs, and conversations during two online forums representing a total of 24 institutions. Findings from these sources are analyzed and synthesized in this report.

https://tinyurl.com/398nzhcx

"Signing Data Citations Enables Data Verification and Citation Persistence"

Increasingly, digital datasets are being published with assigned identifiers, then cited in papers as the basis for repeatable experiments. To help future readers find and verify data, customary citations can be extended with content signatures, which can be introduced without having to replace existing identifier such as DOIs and ARKs. That is, signatures can be seen as complementary identifiers to help keep specific versions of cited data findable and identifiable as they evolve and change locations. For example, if a DOI identifies an evolving dataset, rather than a fixed version — i.e., content drift is expected — the DOI can safely be cited for the sake of attribution, metadata linking, and citation statistics (e.g., by Crossref (https://www.crossref.org) and DataCite (https://datacite.org)), while the content signature helps the reader find the exact content that was cited, possibly with assistance from metadata linked to the DOI. Additionally, a citation that includes both the DOI (for example) and content signature of a dataset creates a fixed mapping between the two identifiers. Then, unintentional content drift by the DOI can be detected and reported, and an alternative location may potentially be discovered by consulting public content signature registries.

https://doi.org/10.1038/s41597-023-02230-y

"Perceived Benefits of Open Data Are Improving but Scientists Still Lack Resources, Skills, and Rewards"

Addressing global scientific challenges requires the widespread sharing of consistent and trustworthy research data. Identifying the factors that influence widespread data sharing will help us understand the limitations and potential leverage points. We used two well-known theoretical frameworks, the Theory of Planned Behavior and the Technology Acceptance Model, to analyze three DataONE surveys published in 2011, 2015, and 2020. These surveys aimed to identify individual, social, and organizational influences on data-sharing behavior. In this paper, we report on the application of multiple factor analysis (MFA) on this combined, longitudinal, survey data to determine how these attitudes may have changed over time. The first two dimensions of the MFA were named willingness to share and satisfaction with resources based on the contributing questions and answers. Our results indicated that both dimensions are strongly influenced by individual factors such as perceived benefit, risk, and effort. Satisfaction with resources was significantly influenced by social and organizational factors such as the availability of training and data repositories. Researchers that improved in willingness to share are shown to be operating in domains with a high reliance on shared resources, are reliant on funding from national or federal sources, work in sectors where internal practices are mandated, and live in regions with highly effective communication networks. Significantly, satisfaction with resources was inversely correlated with willingness to share across all regions. We posit that this relationship results from researchers learning what resources they actually need only after engaging with the tools and procedures extensively.

https://doi.org/10.1057/s41599-023-01831-7

Video: "Dryad in the Community: New Data Sharing Mandates and the Role of Academic Libraries"

In this presentation, Dryad’s Head of Community Engagement, Sarah Lippincott is joined by fellow presenters Michael Casp, Head of Production Division at J&J Editorial, Emma Molls, Director of Open Research & Publishing at University of Minnesota Libraries, and Alberto Pepe, Director of Strategy and Innovation at Wiley and Co-founder of Authorea. Sarah reviews some pertinent highlights from the Nelson memo and NIH policies, two of the major developments that will impact data sharing over the next few years. and concludes with a discussion on how libraries can help researchers move from data sharing to data publishing.

https://tinyurl.com/bdfd7axh

"It Takes a Researcher to Know a Researcher: Academic Librarian Perspectives Regarding Skills and Training for Research Data Support in Canada "

This study demonstrates that an in-depth qualitative portrait of data-related librarians within a national academic ecosystem provides valuable new insights regarding the perceived importance of conducting original empirical research to succeed in these roles.

https://doi.org/10.18438/eblip30297

University of Hawaii at Manoa: Needs Assessment for Data Management and Sharing Training Courses

Data management is an increasingly fundamental skill for graduate students and researchers in the biomedical sciences, especially as National Institutes of Health (NIH) and other funding agencies are now beginning to require data management and sharing plans as part of research. Since the University of Hawaii at Manoa (UHM) Library provided little support for this area and existing data management and sharing instructional content are either out of date or fail to address the unique needs of the UHM research community, the UHM Library took steps to establish data management and sharing instruction services to meet the specific needs of the UHM research community.

https://hdl.handle.net/10125/104944

"DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization"

Data users need relevant context and research expertise to effectively search for and identify relevant datasets. Leading data providers, such as the Inter-university Consortium for Political and Social Research (ICPSR), offer standardized metadata and search tools to support data search. Metadata standards emphasize the machine-readability of data and its documentation. There are opportunities to enhance dataset search by improving users’ ability to learn about, and make sense of, information about data. Prior research has shown that context and expertise are two main barriers users face in effectively searching for, evaluating, and deciding whether to reuse data. In this paper, we propose a novel chatbot-based search system, DataChat, that leverages a graph database and a large language model to provide novel ways for users to interact with and search for research data. DataChat complements data archives’ and institutional repositories’ ongoing efforts to curate, preserve, and share research data for reuse by making it easier for users to explore and learn about available research data.

https://arxiv.org/abs/2305.18358

Digital Scholarship Has Released the Academic Libraries and Research Data Management Bibliography

The Academic Libraries and Research Data Management Bibliography includes over 345 selected English-language articles and books that are useful in understanding how academic libraries plan for, implement, provide, evaluate, and conduct studies about research data management (RDM) services. Most sources have been published from 2012 through 2023. It includes full abstracts for works under certain Creative Commons Licenses. It is available as a website and a website PDF with live links.

Digital Scholarship’s other bibliographies about research data curation include the Research Data Curation and Management Bibliography (over 800 works), the Research Data Publication and Citation Bibliography (over 225 works), and the Research Data Sharing and Reuse Bibliography (over 200 works).

"FAIR in Action — A Flexible Framework to Guide FAIRification"

The COVID-19 pandemic has highlighted the need for FAIR (Findable, Accessible, Interoperable, and Reusable) data more than any other scientific challenge to date. We developed a flexible, multi-level, domain-agnostic FAIRification framework, providing practical guidance to improve the FAIRness for both existing and future clinical and molecular datasets. We validated the framework in collaboration with several major public-private partnership projects, demonstrating and delivering improvements across all aspects of FAIR and across a variety of datasets and their contexts. We therefore managed to establish the reproducibility and far-reaching applicability of our approach to FAIRification tasks.

https://doi.org/10.1038/s41597-023-02167-2

"Rethinking Transparency and Rigor from a Qualitative Open Science Perspective"

To further complicate matters, many qualitative researchers would posit that while secondary data are a combination of the researcher’s perceptions and observations, even primary data, such as interview transcripts, are filtered to some extent through the researcher. This is because, in qualitative research, the researcher is an instrument of both data collection and analysis . . . .

The researcher-as-instrument tradition also complicates discussions around reproducibility (i.e., the ability for another researcher to look at someone’s data and reproduce the analyses), one of the key components of rigor as it is currently discussed in the open science movement (NIH, n.d.). Quantitative researchers’ focus on reproducibility is often contrary to the tenets of qualitative research, particularly in methodologies aiming to uncover new ways of knowing, such as constructivist and grounded theory approaches. If one understands the researcher as a data collection instrument and a filter through which data is processed, strict quantitative-focused reproducibility becomes less likely—not through misconduct or error, but because ultimately, people conduct research, and people are not likely to have exactly the same perspectives. Guidelines that reinforce reproducibility without addressing this tension are not going to be useful for all researchers.

https://bit.ly/3MEbtnk

"A Pilot Study to Locate Historic Scientific Data in a University Archive"

Historic data in analog (or print) format is a valuable resource that is utilized by scientists in many fields. This type of data may be found in various locations on university campuses including offices, labs, storage facilities, and archives. This study investigates whether biological data held in one institutional university archives could be identified, described, and thus made potentially useful for contemporary life scientists. Scientific data was located and approximately half of it was deemed to be of some value to current researchers and about 20% included enough information for the study to be repeated. Locating individual data sets in the collections at the University Archives at the University of Minnesota proved challenging. This preliminary work points to possible ways to move forward to make raw data in university archives collections more discoverable and likely to be reused. It raises questions that can help inform future work in this area.

https://bit.ly/41JBMNb

"Initial Insight Into Three Modes of Data Sharing: Prevalence of Primary Reuse, Data Integration and Dataset Release in Research Articles"

While data sharing has received research interest in recent times, its real status remains unclear, owing to its ambiguous concept. To understand the current status of data sharing, this study examined primary reuse, data integration, and dataset release as the actual practices of data sharing. A total of 963 articles, chosen from those published in 2018 and registered in the Web of Science global citation database, were manually checked. Existing data were reused in the mode of data integration (13.3%) as frequently as they were for the mode of primary reuse (12.1%). Dataset release was the least common mode (9.0%). The results show the variation in data sharing and indicate the need for standardization of data description in articles based on thorough registration and expansion in public data archives to close the loop that results in the virtuous cycle of research data.

https://doi.org/10.1002/leap.1546