Archives des mots-clés : research data management

Research data management policy and practice in Chinese university libraries

Posté le par

Authors : Yingshen Huang, Andrew M. Cox, Laura Sbaffi

On April 2, 2018, the State Council of China formally released a national Research Data Management (RDM) policy “Measures for Managing Scientific Data”. In this context and given that university libraries have played an important role in supporting RDM at an institutional level in North America, Europe, and Australasia, the aim of this article is to explore the current status of RDM in Chinese universities, in particular how university libraries have been involved in taking the agenda forward.

This article uses a mixed‐methods data collection approach and draws on a website analysis of university policies and services; a questionnaire for university librarians; and semi‐structured interviews. Findings indicate that Research Data Service at a local level in Chinese Universities are in their infancy.

There is more evidence of activity in developing data repositories than support services. There is little development of local policy. Among the explanations of this may be the existence of a national‐level infrastructure for some subject disciplines, the lack of professionalization of librarianship, and the relatively weak resonance of openness as an idea in the Chinese context.

URL : Research data management policy and practice in Chinese university libraries

DOI : https://doi.org/10.1002/asi.24413

Données à penser. Enjeux pratiques et éthiques autour des données dans le montage de projets de recherche européens

Posté le par

Auteurs/Authors : Delphine Cavallo, Camille Noûs

Cet article prend la forme d’un retour d’expérience sur le montage de projets de recherche européens, en déroulant les enchaînements entre objectifs, contraintes et prises de décisions autour de deux cas concrets.

Il montre comment les acteurs de ces projets – porteurs et porteuses scientifiques comme ingénieur-e-s – tentent de penser une réponse à la fois scientifique, documentaire, technologique et éthique aux exigences de la Commission européenne en matière de gestion des données de la recherche, à un moment où ces exigences ne correspondent ni à des métiers et pratiques intégrés dans les structures de recherche, ni à des routines ou des besoins identifiés parmi les équipes de recherche.

Il plaide pour la prise en compte conjointe entre chercheurs et chercheuses et ingénieur-e-s des enjeux éthiques liés à la gestion des données dès le montage des projets.

DOI : https://doi.org/10.4000/traces.10793

Models for Engaging Liaisons in Research Data Services

Posté le par

Authors : Megan Sapp Nelson, Abigail Goben

Research data services in academic libraries is often perceived as the purview of liaison librarians. A variety of models has emerged by which these services may be developed or implemented.

These include hierarchical models and those based more on individual interest. Of critical importance with any model, however, is the identification of support and opportunities for engagement from library administration and management in order to grow and assess the implementation of research data services.

URL : Models for Engaging Liaisons in Research Data Services

DOI : https://doi.org/10.7710/2162-3309.2382

Research Data Management for Master’s Students: From Awareness to Action

Posté le par

Authors: Daen Adriaan Ben Smits, Marta Teperek

This article provides an analysis of how sixteen recently graduated master’s students from the Netherlands perceive research data management. It is important to study the master’s students’ attitudes towards this, as students in this phase prepare themselves for their career. Some of them might become future academics or policymakers, thus, potentially, the future advocates of good data management and reproducible science.

In general, students were rather unsure what ‘data management’ meant and would often confuse it with data analysis, study design or methodology, or ethics and privacy. When students defined the concept, they focussed on privacy aspects. Concepts such as open data and the ‘FAIR’ principles were rarely mentioned, even though these are the cornerstones of contemporary data management efforts.

In practice, the students managed their own data in an ad hoc way, and only a few of them worked with a clear data management plan. Illustrative of this is that half of the interviewees did not know where to find their data anymore. Furthermore, their study programmes had diverse approaches to data management education.

Most of the classes offered were limited in scope. Nevertheless, the students seemed to be aware of the importance of data management and were willing to learn more about good data management practices.

This report helps to catch an important first glimpse of how master’s students (from different scientific backgrounds) think about research data management. Only by knowing this, accurate measures can be taken to improve data management awareness and skills.

The article also provides some useful recommendations on what such measures might be, and introduces some of the steps already taken by the Delft University of Technology (TU Delft).

URL : Research Data Management for Master’s Students: From Awareness to Action

DOI : http://doi.org/10.5334/dsj-2020-030

Research Data Management Status of Science and Technology Research Institutes in Korea

Posté le par

Authors : Myung-seok Choi, Sanghwan Lee

Recent advances in digital technology and the data-driven science paradigm has led to a proliferation of research data, which are becoming more important in scholarly communications.

The sharing and reuse of research data can play a key role in enhancing the reusability and reproducibility of research, and data from publicly funded projects are assumed to be public goods. This is seen as a movement of open science and, more specifically, open research data.

Many countries, such as the USA, UK, and Australia, are pushing ahead with implementing policies and infrastructure for open research data. In this paper, we present survey results pertaining to the creation, management, and utilization of data for researchers from government-funded research institutes of science and technology in Korea.

We then introduce recent regulations stipulating a mandated data management plan for national R&D projects and on-going efforts to realize open research data in Korea.

URL : Research Data Management Status of Science and Technology Research Institutes in Korea

DOI : http://doi.org/10.5334/dsj-2020-029

Foundational Practices of Research Data Management

Posté le par

Authors : Kristin A Briney, Heather Coates, Abigail Goben

The importance of research data has grown as researchers across disciplines seek to ensure reproducibility, facilitate data reuse, and acknowledge data as a valuable scholarly commodity.

Researchers are under increasing pressure to share their data for validation and reuse. Adopting good data management practices allows researchers to efficiently locate their data, understand it, and use it throughout all of the stages of a project and in the future. Additionally, good data management can streamline data analysis, visualization, and reporting, thus making publication less stressful and time-consuming.

By implementing foundational practices of data management, researchers set themselves up for success by formalizing processes and reducing common errors in data handling, which can free up more time for research. This paper provides an introduction to best practices for managing all types of data.

URL : Foundational Practices of Research Data Management

DOI : https://doi.org/10.3897/rio.6.e56508

Research Data Management as an Integral Part of the Research Process of Empirical Disciplines Using Landscape Ecology as an Example

Posté le par

Authors : Winfried Schröder, Stefan Nickel

Research Data Management (RDM) is regarded as an elementary component of empirical disciplines. Taking Landscape Ecology in Germany as an example the article demonstrates how to integrate RDM into the research design as a complement of the classic quality control and assurance in empirical research that has, so far, generally been limited to data production.

Sharing and reuse of empirical data by scientists as well as thorough peer reviews of knowledge produced by empirical research requires that the problem of the research in question, the operationalized definitions of the objects of investigation and their representative selection are documented and archived as well as the methods of data production including indicators for data quality and all data collected and produced.

On this basis, the extent to which this complemented design of research processes has already been realized is demonstrated by research projects of the Chair of Landscape Ecology at the University of Vechta, Germany.

This study is part of a joined research project on Research Data Management funded by the German Federal Ministry of Education and Research.

URL : Research Data Management as an Integral Part of the Research Process of Empirical Disciplines Using Landscape Ecology as an Example

DOI : http://doi.org/10.5334/dsj-2020-026