Archives des mots-clés : research data management

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

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

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

 

A Review of the History, Advocacy and Efficacy of Data Management Plans

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Authors: Nicholas Andrew Smale, Kathryn Unsworth, Gareth Denyer, Elise Magatova, Daniel Barr

Data management plans (DMPs) have increasingly been encouraged as a key component of institutional and funding body policy. Although DMPs necessarily place administrative burden on researchers, proponents claim that DMPs have myriad benefits, including enhanced research data quality, increased rates of data sharing, and institutional planning and compliance benefits.

In this article, we explore the international history of DMPs and describe institutional and funding body DMP policy. We find that economic and societal benefits from presumed increased rates of data sharing was the original driver of mandating DMPs by funding bodies.

Today, 86% of UK Research Councils and 63% of US funding bodies require submission of a DMP with funding applications. Given that no major Australian funding bodies require DMP submission, it is of note that 37% of Australian universities have taken the initiative to internally mandate DMPs. Institutions both within Australia and internationally frequently promote the professional benefits of DMP use, and endorse DMPs as ‘best practice’.

We analyse one such typical DMP implementation at a major Australian institution, finding that DMPs have low levels of apparent translational value. Indeed, an extensive literature review suggests there is very limited published systematic evidence that DMP use has any tangible benefit for researchers, institutions or funding bodies.

We are therefore led to question why DMPs have become the go-to tool for research data professionals and advocates of good data practice. By delineating multiple use-cases and highlighting the need for DMPs to be fit for intended purpose, we question the view that a good DMP is necessarily that which encompasses the entire data lifecycle of a project.

Finally, we summarise recent developments in the DMP landscape, and note a positive shift towards evidence-based research management through more researcher-centric, educative, and integrated DMP services.

URL : A Review of the History, Advocacy and Efficacy of Data Management Plans

DOI : https://doi.org/10.2218/ijdc.v15i1.525

Alter-Value in Data Reuse: Non-Designated Communities and Creative Processes

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Author : Guillaume Boutard

This paper builds on the investigation of data reuse in creative processes to discuss ‘epistemic pluralism’ and data ‘alter-value’ in research data management. Focussing on a specific non-designated community, we conducted semi-structured interviews with five artists in relation to five works.

Data reuse is a critical component of all these works. The qualitative content analysis brings to light agonistic-antagonistic practices in data reuse and shows multiple deconstructions of the notion of data value as it is portrayed in the data reuse literature.

Finally, the paper brings to light the benefits of including such practices in the conceptualization of data curation.

URL : Alter-Value in Data Reuse: Non-Designated Communities and Creative Processes

DOI : http://doi.org/10.5334/dsj-2020-023

Comparing the diffusion and adoption of linked data and research data management services among libraries

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Author : Jinfang Niu

Introduction

Libraries face innovations periodically. It is important to identify consistent patterns in the diffusion and adoption of innovations so that libraries and relevant stakeholders will be informed and well-prepared for future innovations.

Method

This paper compares findings from two previous projects, each of which was conducted to investigate the diffusion and adoption of two recent innovations, research data management service and linked data, respectively.

The two projects were conducted using similar methods: collecting and analysing literature about the adoption of these innovations in libraries in the United States. Literature was collected through Google Scholar search, citation chasing, and target search for people or libraries that are involved in their adoption.

Analysis

The gathered articles were then coded and analysed based on diffusion of innovation theories.

Results

Similarities and disparities between the diffusion and adoption of the two innovations were identified.

Conclusions

Findings from this study are informative for the decision-making of libraries, librarians, funders, and professional associations facing future innovations. They also contribute to diffusion of innovation theories through revealing new communication channels and alternative adoption processes, as well as redefining existing concepts.

URL : http://www.informationr.net/ir/25-2/paper855.html

Why You Need Soft and Non-Technical Skills for Successful Data Librarianship

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Author : Margaret Henderson

There are many courses available to teach research data management to librarians and researchers. While these courses can help with technical skills, like programming or statistics, and practical knowledge of data life cycles or data sharing policies, there are “soft skills” and non-technical skills that are needed to successfully start and run data services.

While there are many important characteristics of a good data librarian, reference skills, relationship building, collaboration, listening, and facilitation are some of the most important. Giving consideration to these skills will help any data librarian with their multifaceted job.

URL : Skills for Data Librarianship

DOI : https://doi.org/10.7191/jeslib.2020.1183