Are Research Datasets FAIR in the Long Run?

Authors : Dennis Wehrle, Klaus Rechert

Currently, initiatives in Germany are developing infrastructure to accept and preserve dissertation data together with the dissertation texts (on state level – bwDATA Diss, on federal level – eDissPlus).

In contrast to specialized data repositories, these services will accept data from all kind of research disciplines. To ensure FAIR data principles (Wilkinson et al., 2016), preservation plans are required, because ensuring accessibility, interoperability and re-usability even for a minimum ten year data redemption period can become a major challenge.

Both for longevity and re-usability, file formats matter. In order to ensure access to data, the data’s encoding, i.e. their technical and structural representation in form of file formats, needs to be understood. Hence, due to a fast technical lifecycle, interoperability, re-use and in some cases even accessibility depends on the data’s format and our future ability to parse or render these.

This leads to several practical questions regarding quality assurance, potential access options and necessary future preservation steps. In this paper, we analyze datasets from public repositories and apply a file format based long-term preservation risk model to support workflows and services for non-domain specific data repositories.

URL : Are Research Datasets FAIR in the Long Run?

DOI : https://doi.org/10.2218/ijdc.v13i1.659

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

Research data management in the French National Research Center (CNRS)

Authors : Joachim Schöpfel, Coline Ferrant, Francis Andre, Renaud Fabre

Purpose

The purpose of this paper is to present empirical evidence on the opinion and behaviour of French scientists (senior management level) regarding research data management (RDM).

Design/methodology/approach

The results are part of a nationwide survey on scientific information and documentation with 432 directors of French public research laboratories conducted by the French Research Center CNRS in 2014.

Findings

The paper presents empirical results about data production (types), management (human resources, IT, funding, and standards), data sharing and related needs, and highlights significant disciplinary differences.

Also, it appears that RDM and data sharing is not directly correlated with the commitment to open access. Regarding the FAIR data principles, the paper reveals that 68 per cent of all laboratory directors affirm that their data production and management is compliant with at least one of the FAIR principles.

But only 26 per cent are compliant with at least three principles, and less than 7 per cent are compliant with all four FAIR criteria, with laboratories in nuclear physics, SSH and earth sciences and astronomy being in advance of other disciplines, especially concerning the findability and the availability of their data output.

The paper concludes with comments about research data service development and recommendations for an institutional RDM policy.

Originality/value

For the first time, a nationwide survey was conducted with the senior research management level from all scientific disciplines. Surveys on RDM usually assess individual data behaviours, skills and needs. This survey is different insofar as it addresses institutional and collective data practice.

The respondents did not report on their own data behaviours and attitudes but were asked to provide information about their laboratory. The response rate was high (>30 per cent), and the results provide good insight into the real support and uptake of RDM by senior research managers who provide both models (examples for good practice) and opinion leadership.

URL : https://hal.univ-lille3.fr/hal-01728541/

From Open Access to Open Data: collaborative work in the university libraries of Catalonia

Authors: Mireia Alcalá Ponce de León, Lluís Anglada i de Ferrer

In the last years, the scientific community and funding bodies have paid attention to collected, generated or used data throughout different research activities. The dissemination of these data becomes one of the constituent elements of Open Science.

For this reason, many funders are requiring or promoting the development of Data Management Plans, and depositing open data following the FAIR principles (Findable, Accessible, Interoperable and Reusable).

Libraries and research offices of Catalan universities –which coordinately work within the Open Science Area of CSUC– offer support services to research data management. The different works carried out at the Consortium level will be presented, as well the implementation of the service in each university.

URL : From Open Access to Open Data: collaborative work in the university libraries of Catalonia

DOI : http://doi.org/10.18352/lq.10253

Supporting FAIR Data Principles with Fedora

Author: David Wilcox

Making data findable, accessible, interoperable, and re-usable is an important but challenging goal. From an infrastructure perspective, repository technologies play a key role in supporting FAIR data principles.

Fedora is a flexible, extensible, open source repository platform for managing, preserving, and providing access to digital content. Fedora is used in a wide variety of institutions including libraries, museums, archives, and government organizations.

Fedora provides native linked data capabilities and a modular architecture based on well-documented APIs and ease of integration with existing applications. As both a project and a community, Fedora has been increasingly focused on research data management, making it well-suited to supporting FAIR data principles as a repository platform.

Fedora provides strong support for persistent identifiers, both by minting HTTP URIs for each resource and by allowing any number of additional identifiers to be associated with resources as RDF properties.

Fedora also supports rich metadata in any schema that can be indexed and disseminated using a variety of protocols and services. As a linked data server, Fedora allows resources to be semantically linked both within the repository and on the broader web.

Along with these and other features supporting research data management, the Fedora community has been actively participating in related initiatives, most notably the Research Data Alliance.

Fedora representatives participate in a number of interest and working groups focused on requirements and interoperability for research data repository platforms.

This participation allows the Fedora project to both influence and be influenced by an international group of Research Data Alliance stakeholders. This paper will describe how Fedora supports FAIR data principles, both in terms of relevant features and community participation in related initiatives.

URL : Supporting FAIR Data Principles with Fedora

DOI : http://doi.org/10.18352/lq.10247