Archives des mots-clés : research data

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

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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

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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

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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

Responsible, practical genomic data sharing that accelerates research

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Authors : James Brian Byrd, Anna C. Greene, Deepashree Venkatesh Prasad, Xiaoqian Jiang, Casey S. Greene

Data sharing anchors reproducible science, but expectations and best practices are often nebulous. Communities of funders, researchers and publishers continue to grapple with what should be required or encouraged.

To illuminate the rationales for sharing data, the technical challenges and the social and cultural challenges, we consider the stakeholders in the scientific enterprise. In biomedical research, participants are key among those stakeholders.

Ethical sharing requires considering both the value of research efforts and the privacy costs for participants. We discuss current best practices for various types of genomic data, as well as opportunities to promote ethical data sharing that accelerates science by aligning incentives.

URL : Responsible, practical genomic data sharing that accelerates research

DOI : https://doi.org/10.1038/s41576-020-0257-5

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

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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

Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences

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Authors : Rebecca Springer, Danielle Cooper

There is a growing perception that science can progress more quickly, more innovatively, and more rigorously when researchers share data with each other. However many scientists are not engaging in data sharing and remain skeptical of its relevance to their work.

As organizations and initiatives designed to promote STEM data sharing multiply – within, across, and outside academic institutions – there is a pressing need to decide strategically on the best ways to move forward. In this paper, we propose a new mechanism for conceptualizing and supporting STEM research data sharing.

Successful data sharing happens within data communities, formal or informal groups of scholars who share a certain type of data with each other, regardless of disciplinary boundaries. Drawing on the findings of four large-scale qualitative studies of research practices conducted by Ithaka S+R, as well as the scholarly literature, we identify what constitutes a data community and outline its most important features by studying three success stories, investigating the circumstances under which intensive data sharing is already happening.

We contend that stakeholders who wish to promote data sharing – librarians, information technologists, scholarly communications professionals, and research funders, to name a few – should work to identify and empower emergent data communities.

These are groups of scholars for whom a relatively straightforward technological intervention, usually the establishment of a data repository, could kickstart the growth of a more active data sharing culture. We conclude by offering recommendations for ways forward.

URL : Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences

DOI : https://doi.org/10.2218/ijdc.v15i1.695

Understanding the Data Management Plan as a Boundary Object through a Multi-stakeholder perspective

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Authors : Live Kvale, Nils Pharo

A three-phase Delphi study was used to investigate an emerging community for research data management in Norway and their understanding and application of data management plans (DMPs). The findings reveal visions of what the DMP should be as well as different practice approaches, yet the stakeholders present common goals.

This paper discusses the different perspectives on the DMP by applying Star and Griesemer’s theory of boundary objects (Star & Griesemer, 1989). The debate on what the DMP is and the findings presented are relevant to all research communities currently implementing DMP procedures and requirements. The current discussions about DMPs tend to be distant from the active researchers and limited to the needs of funders and institutions rather than to the usefulness for researchers.

By analysing the DMP as a boundary object, plastic and adaptable yet with a robust identity (Star & Griesemer, 1989), and by translating between worlds where collaboration on data sharing can take place we expand the perspectives and include all stakeholders. An understanding of the DMP as a boundary object can shift the focus from shaping a DMP which fulfils funders’ requirements to enabling collaboration on data management and sharing across domains using standardised forms.

URL : Understanding the Data Management Plan as a Boundary Object through a Multi-stakeholder perspective

DOI: https://doi.org/10.2218/ijdc.v15i1.729