Archives des mots-clés : research data

Trust, Respect, and Reciprocity : Informing Culturally Appropriate Data-Sharing Practice in Vietnam

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International science funders and publishers are driving a growing trend in data sharing. There is mounting pressure on researchers in low- and middle-income settings to conform to new sharing policies, despite minimal empirically grounded accounts of the ethical challenges of implementing the policies in these settings.

This study used in-depth interviews and focus group discussions with 48 stakeholders in Vietnam to explore the experiences, attitudes, and expectations that inform ethical and effective approaches to sharing clinical research data. Distinct views on the role of trust, respect, and reciprocity were among those that emerged to inform culturally appropriate best practices. We conclude by discussing the challenges that authors of data-sharing policies should consider in this unique context.

URL : Trust, Respect, and Reciprocity

Alternative location : http://m.jre.sagepub.com/content/10/3/251

Sweat, Skepticism, and Uncharted Territory : A Qualitative Study of Opinions on Data Sharing Among Public Health Researchers and Research Participants in Mumbai, India

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Efforts to internalize data sharing in research practice have been driven largely by developing international norms that have not incorporated opinions from researchers in low- and middle-income countries. We sought to identify the issues around ethical data sharing in the context of research involving women and children in urban India. We interviewed researchers, managers, and research participants associated with a Mumbai non-governmental organization, as well as researchers from other organizations and members of ethics committees.

We conducted 22 individual semi-structured interviews and involved 44 research participants in focus group discussions. We used framework analysis to examine ideas about data and data sharing in general; its potential benefits or harms, barriers, obligations, and governance; and the requirements for consent. Both researchers and participants were generally in favor of data sharing, although limited experience amplified their reservations. We identified three themes: concerns that the work of data producers may not receive appropriate acknowledgment, skepticism about the process of sharing, and the fact that the terrain of data sharing was essentially uncharted and confusing.

To increase data sharing in India, we need to provide guidelines, protocols, and examples of good practice in terms of consent, data preparation, screening of applications, and what individuals and organizations can expect in terms of validation, acknowledgment, and authorship.

URL : Sweat, Skepticism, and Uncharted Territory

Alternative location : http://m.jre.sagepub.com/content/10/3/239

Views of Ethical Best Practices in Sharing Individual-Level Data From Medical and Public Health Research : A Systematic Scoping Review

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There is increasing support for sharing individual-level data generated by medical and public health research. This scoping review of empirical research and conceptual literature examined stakeholders’ perspectives of ethical best practices in data sharing, particularly in low- and middle-income settings. Sixty-nine empirical and conceptual articles were reviewed, of which, only five were empirical studies and eight were conceptual articles focusing on low- and middle-income settings.

We conclude that support for sharing individual-level data is contingent on the development and implementation of international and local policies and processes to support ethical best practices. Further conceptual and empirical research is needed to ensure data sharing policies and processes in low- and middle-income settings are appropriately informed by stakeholders’ perspectives.

URL : Views of Ethical Best Practices in Sharing Individual-Level Data From Medical and Public Health Research

Alternative location : http://m.jre.sagepub.com/content/10/3/225

Sharing Public Health Research Data: Toward the Development of Ethical Data-Sharing Practice in Low- and Middle-Income Settings

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It is increasingly recognized that effective and appropriate data sharing requires the development of models of good datasharing practice capable of taking seriously both the potential benefits to be gained and the importance of ensuring that the rights and interests of participants are respected and that risk of harms is minimized. Calls for the greater sharing of individual-level data from biomedical and public health research are receiving support among researchers and research funders. Despite its potential importance, data sharing presents important ethical, social, and institutional challenges in low-income settings.

In this article, we report on qualitative research conducted in five low- and middle-income countries exploring the experiences of key research stakeholders and their views about what constitutes good data-sharing practice.

URL : Sharing Public Health Research Data

Alternative location : http://m.jre.sagepub.com/content/10/3/217

Assessment of Data Management Services at New England Region Resource Libraries

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Objective

To understand how New England medical libraries are addressing scientific research data management and providing services to their communities.

Setting

The National Network of Libraries of Medicine, New England Region (NN/LM NER) contains 17 Resource Libraries. The University of Massachusetts Medical School serves as the New England Regional Medical Library (RML). Sixteen of the NER Resource Libraries completed this survey.

Methods

A 40-question online survey assessed libraries’ services and programs for providing research data management education and support. Libraries shared their current plans and institutional challenges associated with developing data services.

Results

This study shows few NER Resource Libraries currently integrate scientific research data management into their services and programs, and highlights the region’s use of resources provided by the NN/LM NER RML at the University of Massachusetts Medical School.

Conclusions

Understanding the types of data services being delivered at NER libraries helps to inform the NN/LM NER about the eScience learning needs of New England medical librarians and helps in the planning of professional development programs that foster effective biomedical research data services.

URL : Assessment of Data Management Services at New England Region Resource Libraries

DOI : http://dx.doi.org/10.7191/jeslib.2015.1068

Knowledge Infrastructures in Science: Data, Diversity, and Digital Libraries

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Digital libraries can be deployed at many points throughout the life cycles of scientific research projects from their inception through data collection, analysis, documentation, publication, curation, preservation, and stewardship. Requirements for digital libraries to manage research data vary along many dimensions, including life cycle, scale, research domain, and types and degrees of openness.

This article addresses the role of digital libraries in knowledge infrastructures for science, presenting evidence from long-term studies of four research sites. Findings are based on interviews (n=208), ethnographic fieldwork, document analysis, and historical archival research about scientific data practices, conducted over the course of more than a decade.

The Transformation of Knowledge, Culture, and Practice in Data-Driven Science: A Knowledge Infrastructures Perspective project is based on a 2×2 design, comparing two “big science” astronomy sites with two “little science” sites that span physical sciences, life sciences, and engineering, and on dimensions of project scale and temporal stage of life cycle.

The two astronomy sites invested in digital libraries for data management as part of their initial research design, whereas the smaller sites made smaller investments at later stages. Role specialization varies along the same lines, with the larger projects investing in information professionals, and smaller teams carrying out their own activities internally. Sites making the largest investments in digital libraries appear to view their datasets as their primary scientific legacy, while other sites stake their legacy elsewhere. Those investing in digital libraries are more concerned with the release and reuse of data; types and degrees of openness vary accordingly.

The need for expertise in digital libraries, data science, and data stewardship is apparent throughout all four sites. Examples are presented of the challenges in designing digital libraries and knowledge infrastructures to manage and steward research data.

URL : http://works.bepress.com/borgman/371/

Sizing the Problem of Improving Discovery and Access to NIH-Funded Data: A Preliminary Study

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Objective

This study informs efforts to improve the discoverability of and access to biomedical datasets by providing a preliminary estimate of the number and type of datasets generated annually by research funded by the U.S. National Institutes of Health (NIH). It focuses on those datasets that are “invisible” or not deposited in a known repository.

Methods

We analyzed NIH-funded journal articles that were published in 2011, cited in PubMed and deposited in PubMed Central (PMC) to identify those that indicate data were submitted to a known repository. After excluding those articles, we analyzed a random sample of the remaining articles to estimate how many and what types of invisible datasets were used in each article.

Results

About 12% of the articles explicitly mention deposition of datasets in recognized repositories, leaving 88% that are invisible datasets. Among articles with invisible datasets, we found an average of 2.9 to 3.4 datasets, suggesting there were approximately 200,000 to 235,000 invisible datasets generated from NIH-funded research published in 2011. Approximately 87% of the invisible datasets consist of data newly collected for the research reported; 13% reflect reuse of existing data. More than 50% of the datasets were derived from live human or non-human animal subjects.

Conclusion

In addition to providing a rough estimate of the total number of datasets produced per year by NIH-funded researchers, this study identifies additional issues that must be addressed to improve the discoverability of and access to biomedical research data: the definition of a “dataset,” determination of which (if any) data are valuable for archiving and preservation, and better methods for estimating the number of datasets of interest. Lack of consensus amongst annotators about the number of datasets in a given article reinforces the need for a principled way of thinking about how to identify and characterize biomedical datasets.

URL : Sizing the Problem of Improving Discovery and Access to NIH-Funded Data: A Preliminary Study

DOI : 10.1371/journal.pone.0132735