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

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


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

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



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

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


Usages et pratiques en lien avec les données de recherche. Une enquête menée auprès des chercheurs de l’université Paul-Valéry Montpellier 3

Auteurs/Authors : Hans Dillaerts, Céline Paganelli, Lise Verlaet, Hugo Catherine

Cette enquête s’inscrit dans le cadre du projet de recherche intitulé « Science ouverte et données de la recherche en SHS : entre politiques d’incitation et pratiques de la communication scientifique, quelle place pour les institutions et les bibliothèques ? » qui bénéficie pour une durée de 2 ans d’un financement de l’université Paul-Valéry Montpellier 3.

Le projet vise à recueillir et analyser d’une part les usages et les pratiques des chercheurs de l’université Paul-Valéry Montpellier 3 en matière des données de recherche et d’autre part les pratiques institutionnelles et notamment celles des professionnels de l’IST au sein des structures documentaires et des bibliothèques universitaires.

Une enquête quantitative a été menée en 2019 sur les pratiques et les usages des chercheurs de l’université Paul-Valéry Montpellier 3 en lien avec les données de recherche. L’objectif de ce rapport est de présenter et analyser les résultats de cette enquête qui s’appuie sur un échantillon de 81 réponses complètes.


Data journals: incentivizing data access and documentation within the scholarly communication system

Author : William H. Walters

Data journals provide strong incentives for data creators to verify, document and disseminate their data. They also bring data access and documentation into the mainstream of scholarly communication, rewarding data creators through existing mechanisms of peer-reviewed publication and citation tracking.

These same advantages are not generally associated with data repositories, or with conventional journals’ data-sharing mandates. This article describes the unique advantages of data journals.

It also examines the data journal landscape, presenting the characteristics of 13 data journals in the fields of biology, environmental science, chemistry, medicine and health sciences.

These journals vary considerably in size, scope, publisher characteristics, length of data reports, data hosting policies, time from submission to first decision, article processing charges, bibliographic index coverage and citation impact.

They are similar, however, in their peer review criteria, their open access license terms and the characteristics of their editorial boards.

URL : Data journals: incentivizing data access and documentation within the scholarly communication system


Le principe d’ouverture des données de la recherche scientifique. Réflexions autour du croisement de l’informatique et du droit

Auteur/Author : Agnès Robin

Les données de la recherche scientifique sont actuellement soumises à un programme de standardisation technique (FAIR) dont l’objectif est d’en permettre la diffusion aux fins de réutilisation par le public (entreprises privées ou autre).

Cette politique, qui sans se confondre avec elle, converge avec celle dite de « science ouverte », s’articule autour d’un principe normatif conflictuel, selon lequel le résultats de la recherche (et donc les données) doivent être « aussi ouverts que possibles et pas plus fermés que nécessaire », obligeant alors les chercheurs, ingénieurs et documentalistes, éventuellement chargés de la gestion des données de la recherche, à procéder à une qualification juridique délicate des données.