Étiquette : research data management

Ten principles for machine-actionable data management plans

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

Assessing Data Management Support Needs of Bioengineering and Biomedical Research Faculty

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/

 

Establishing a Research Data Management Service on a Health Sciences Campus

Authors : Kathryn Vela, Nancy Shin

Objective

Given the increasing need for research data management support and education, the Spokane Academic Library at Washington State University (WSU) sought to determine the data management practices, perceptions, and needs of researchers on the WSU Spokane health sciences campus.

Methods

A 23-question online survey was distributed to WSU researchers and research support staff through the campus listserv.

This online survey addressed data organization, documentation, storage & backup, security, preservation, and sharing, as well as challenges and desired support services.

Results

Survey results indicated that there was a clear need for more instruction with regard to data management planning, particularly as data management planning addresses the areas of metadata design, data sharing, data security, and data storage and backup.

Conclusions

This needs assessment will direct how RDM services are implemented on the WSU Spokane campus by the Spokane Academic Library (SAL). These services will influence both research data quality and integrity through improved data management practices.

URL : Establishing a Research Data Management Service on a Health Sciences Campus

DOI : https://doi.org/10.7191/jeslib.2019.1146

Les données de la recherche à l’Université Bordeaux Montaigne : Synthèse d’une enquête qualitative auprès des chercheurs

Auteur/Author : Julie Duprat

Alors que ces dernières années l’importance de l’ouverture des publications écrites par les chercheurs des universités françaises a été largement abordée, les regards se tournent désormais sur une autre de leurs productions avec les données de la recherche.

Dans ce contexte, l’Université Bordeaux Montaigne, spécialisée en sciences humaines et sociales, souhaite mettre en place un service « données de la recherche » afin d’accompagner ses chercheurs dans la gestion et le partage de leurs données de recherche.

Au préalable du service à venir, une enquête a été menée entre septembre et décembre 2018 auprès des chercheurs de l’Université par la conservatrice-stagiaire Julie Duprat afin de faire remonter les besoins du terrain, dans une logique bottom up.

URL : https://hal.archives-ouvertes.fr/hal-02020141

A Principled Approach to Online Publication Listings and Scientific Resource Sharing

Authors : Jacquelijn Ringersma, Karin Kastens, Ulla Tschida, Jos van Berkum

The Max Planck Institute (MPI) for Psycholinguistics has developed a service to manage and present the scholarly output of their researchers. The PubMan database manages publication metadata and full-texts of publications published by their scholars.

All relevant information regarding a researcher’s work is brought together in this database, including supplementary materials and links to the MPI database for primary research data.

The PubMan metadata is harvested into the MPI website CMS (Plone). The system developed for the creation of the publication lists, allows the researcher to create a selection of the harvested data in a variety of formats.

URL : https://journal.code4lib.org/articles/2520

Methods to Evaluate Lifecycle Models for Research Data Management

Authors : Tobias Weber, Dieter Kranzlmüller

Lifecycle models for research data are often abstract and simple. This comes at the danger of oversimplifying the complex concepts of research data management.

The analysis of 90 different lifecycle models lead to two approaches to assess the quality of these models. While terminological issues make direct comparisons of models hard, an empirical evaluation seems possible.

URL : https://arxiv.org/abs/1901.11267

Hors norme ? Une approche normative des données de la recherche

Auteur : Joachim Schöpfel

Nous proposons une réflexion sur le rôle des normes et standards dans la gestion des données de la recherche, dans l’environnement de la politique de la science ouverte.

A partir d’une définition générale des données de la recherche, nous analysons la place et la fonction des normes et standards dans les différentes dimensions du concept des données. En particulier, nous nous intéressons à trois aspects faisant le lien entre le processus scientifique, l’environnement réglementaire et les données de la recherche : les protocoles éthiques, les systèmes d’information recherche et les plans de gestion des données.

A l’échelle internationale, nous décrivons l’effet normatif des principes FAIR qui, par la mobilisation d’autres normes et standards, créent une sorte de « cascade de standards » autour des plateformes et entrepôts, avec un impact direct sur les pratiques scientifiques.

URL : https://revue-cossi.info/numeros/n-5-2018-processus-normalisation-durabilite-information/730-5-2018-schopfel