Archives des mots-clés : research data

Remediation Data Management Plans : A Tool for Recovering Research Data from Messy, Messy Projects

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Author : Clara Llebot

Data Management Plans (DMPs) have been used in the last decade to encourage good data management practices among researchers. DMPs are widely used, preventive tools that encourage good data management practices. DMPs are traditionally used to manage data during the planning stage of the project, often required for grant proposals, and prior to data collection.

In this paper we will use a case study to argue that Data Management Plans can be useful in improving the management of the data of research projects that have moved beyond the planning stage of the research life cycle.

In particular, we focus on the case of active projects where data has already been collected and is still being analyzed.

We discuss the differences and commonalities in structure between preventive Data Management Plans and remedial Data Management Plans, and describe in detail the additional considerations that are needed when writing remedial Data Management Plans: the goals and audience of the document, the data inventory, and an implementation plan.

URL : Remediation Data Management Plans : A Tool for Recovering Research Data from Messy, Messy Projects

DOI : https://doi.org/10.2218/ijdc.v13i1.667

Construction(s) et contradictions des données de recherche en SHS

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Auteurs/Authors : Marie-Laure Malingre, Morgane Mignon, Cécile Pierre, Alexandre Serres

La structuration et le partage des données s’imposent depuis cinq ans au monde de la recherche, à travers des injonctions politiques (de Horizon 2020 au Plan national pour la science ouverte).

L’analyse de l’enquête menée en 2017 auprès des chercheurs de l’université Rennes 2 sur leurs pratiques, représentations et attentes en matière de données conduit à interroger le terme lui-même. Variable et complexe, contrairement à ce que suggère le mot « donnée », la notion ne va pas de soi.

L’article s’efforcera de montrer qu’elle fait l’objet d’une triple construction, épistémologique, intellectuelle et politique, dans les discours des chercheurs et des acteurs institutionnels, en tension avec les pratiques constatées sur le terrain.

DOI : https://www.openscience.fr/Construction-s-et-contradictions-des-donnees-de-recherche-en-SHS#

Building an International Consensus on Multi-Disciplinary Metadata Standards: A CODATA Case History in Nanotechnology

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Authors : John Rumble, John Broome, Simon Hodson

Science today is rapidly becoming both multi-disciplinary and data-driven. These two trends pose new challenges to the capture, management, sharing, and dissemination of research data. Multi-disciplinary science means diverse data generation communities and equally diverse user groups.

Data-driven means that sharing data among different communities is more important than ever because of the growth of modeling and knowledge discovery.

Nanotechnology is a prime example, involving chemistry, physics, materials science, toxicology, environmental science, and many other disciplines. During the past few years, CODATA has created an international, multi-disciplinary Working Group that has developed a number of critically important metadata standards to facilitate sharing nanomaterials data.

In this paper, we discuss the challenges faced in starting and executing this work, as well as the approaches taken to make progress on producing internationally accepted metadata standards.

Many of these approaches are directly applicable to other multi-disciplinary subjects.

URL : Building an International Consensus on Multi-Disciplinary Metadata Standards: A CODATA Case History in Nanotechnology

DOI : http://doi.org/10.5334/dsj-2019-012

Implementing publisher policies that inform, support and encourage authors to share data: two case studies

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Authors: Leila Jones, Rebecca Grant, Iain Hrynaszkiewicz

Open research data is one of the key areas in the expanding open scholarship movement. Scholarly journals and publishers find themselves at the heart of the shift towards openness, with recent years seeing an increase in the number of scholarly journals with data-sharing policies aiming to increase transparency and reproducibility of research.

In this article we present two case studies which examine the experiences that two leading academic publishers, Taylor & Francis and Springer Nature, have had in rolling out data-sharing policies.

We illustrate some of the considerations involved in providing consistent policies across journals of many disciplines, reflecting on successes and challenges.

URL : Implementing publisher policies that inform, support and encourage authors to share data: two case studies

DOI : http://doi.org/10.1629/uksg.463

Ten principles for machine-actionable data management plans

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Authors : Tomasz Miksa, Stephanie Simms, Daniel Mietchen, Sarah Jones

Data management plans (DMPs) are documents accompanying research proposals and project outputs. DMPs are created as free-form text and describe the data and tools employed in scientific investigations. They are often seen as an administrative exercise and not as an integral part of research practice.

There is now widespread recognition that the DMP can have more thematic, machine-actionable richness with added value for all stakeholders: researchers, funders, repository managers, research administrators, data librarians, and others.

The research community is moving toward a shared goal of making DMPs machine-actionable to improve the experience for all involved by exchanging information across research tools and systems and embedding DMPs in existing workflows.

This will enable parts of the DMP to be automatically generated and shared, thus reducing administrative burdens and improving the quality of information within a DMP.

This paper presents 10 principles to put machine-actionable DMPs (maDMPs) into practice and realize their benefits. The principles contain specific actions that various stakeholders are already undertaking or should undertake in order to work together across research communities to achieve the larger aims of the principles themselves.

We describe existing initiatives to highlight how much progress has already been made toward achieving the goals of maDMPs as well as a call to action for those who wish to get involved.

URL : Ten principles for machine-actionable data management plans

DOI : https://doi.org/10.1371/journal.pcbi.1006750

Responsible data sharing in international health research: a systematic review of principles and norms

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Authors : Shona Kalkman, Menno Mostert, Christoph Gerlinger, Johannes J. M. van Delden, Ghislaine J. M. W. van Thiel

Background

Large-scale linkage of international clinical datasets could lead to unique insights into disease aetiology and facilitate treatment evaluation and drug development.

Hereto, multi-stakeholder consortia are currently designing several disease-specific translational research platforms to enable international health data sharing.

Despite the recent adoption of the EU General Data Protection Regulation (GDPR), the procedures for how to govern responsible data sharing in such projects are not at all spelled out yet. In search of a first, basic outline of an ethical governance framework, we set out to explore relevant ethical principles and norms.

Methods

We performed a systematic review of literature and ethical guidelines for principles and norms pertaining to data sharing for international health research.

Results

We observed an abundance of principles and norms with considerable convergence at the aggregate level of four overarching themes: societal benefits and value; distribution of risks, benefits and burdens; respect for individuals and groups; and public trust and engagement.

However, at the level of principles and norms we identified substantial variation in the phrasing and level of detail, the number and content of norms considered necessary to protect a principle, and the contextual approaches in which principles and norms are used.

Conclusions

While providing some helpful leads for further work on a coherent governance framework for data sharing, the current collection of principles and norms prompts important questions about how to streamline terminology regarding de-identification and how to harmonise the identified principles and norms into a coherent governance framework that promotes data sharing while securing public trust.

URL : Responsible data sharing in international health research: a systematic review of principles and norms

DOI : https://doi.org/10.1186/s12910-019-0359-9

Assessing Data Management Support Needs of Bioengineering and Biomedical Research Faculty

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Authors : Christie A. Wiley, Margaret H. Burnette

Objectives

This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of the National Institutes of Health-funded research projects. Specifically, this study seeks to answer the following questions:

  1. What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated?
  2. To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors?
  3. What aspects of data management present the greatest challenges and frustrations?
  4. To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing?
  5. To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas?

Methods

Librarians on the University of Illinois at Urbana Champaign campus conducted semi-structured interviews with bioengineering and biomedical researchers to explore researchers’ knowledge of data management best practices, awareness of library campus services, data management behavior and challenges managing research data.

The topics covered during the interviews were current research projects, data types, format, description, campus repository usage, data-sharing, awareness of library campus services, data reuse, the anticipated impact of health on public and challenges (interview questions are provided in the Appendix).

Results

This study revealed the majority of researchers explore broad research topics, various file storage solutions, generate numerous amounts of data and adhere to differing discipline-specific practices. Researchers expressed both familiarity and unfamiliarity with DMP Tool.

Roughly half of the researchers interviewed reported having documented protocols for file names, file backup, and file storage. Findings also suggest that there is ambiguity about what it means to share research data and confusion about terminology such as “repository” and “data deposit”. Many researchers equate publication to data sharing.

Conclusions

The interviews reveal significant data literacy gaps that present opportunities for library instruction in the areas of file organization, project workflow and documentation, metadata standards, and data deposit options.

The interviews also provide invaluable insight into biomedical and bioengineering research in general and contribute to the authors’ understanding of the challenges facing the researchers we strive to support.

URL : Assessing Data Management Support Needs of Bioengineering and Biomedical Research Faculty

Alternative location  : https://escholarship.umassmed.edu/jeslib/vol8/iss1/1/