Archives des mots-clés : research data management

Création d’un prototype de jeu sérieux sur la gestion des données de la recherche

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Autrices/Authors : Myriam Jouha, Pauline Mell, Alexia Tromber

Les professionnel-le-s de l’information travaillant en bibliothèque académique sont désormais régulièrement amené-e-s à accompagner des chercheurs et chercheuses dans la gestion de leurs données de recherche.

Dans le but d’offrir à ces professionnel-le-s une formation introductive sur cette thématique, nous avons conçu et testé un prototype de jeu sérieux. Ce projet a été réalisé dans le cadre du Master en Sciences de l’information à la Haute école de gestion de Genève.

Méthode : Notre méthodologie s’inspire de deux modèles de conception de jeux sérieux. Elle s’articule en trois étapes : (1) la phase de définition, qui présente les résultats de l’analyse des besoins, l’exploration de l’existant et le dispositif de formation ; (2) la production du prototype et les tests effectués ; (3) l’accompagnement et l’évaluation.

Résultats : Le jeu proposé, « Mission GDR : ultime quête avant les fêtes » est inspiré de la série de jeux d’évasion en boîte « Unlock ». Il s’agit d’un jeu collaboratif pour 1 à 4 participant-e-s dont l’objectif est de compléter une feuille de route représentant le cycle de vie des données et les tâches qui s’y rapportent. Cette feuille, accompagnée d’un guide complémentaire rappelant la théorie abordée dans le jeu, peut ensuite être réutilisée comme ressource dans la pratique professionnelle des joueuses et joueurs.

Discussion : Les tests effectués auprès de personnes aux profils divers démontrent que le jeu est apprécié pour ses aspects ludiques tout en offrant un apport théorique introductif. Initialement prévu pour les professionnel-le-s de l’informations, il pourrait également être proposé à d’autres personnes concernées par la gestion des données, notamment des équipes de recherche. Conçu pour être indépendant d’une session de formation, il est cependant tout à fait envisageable de l’intégrer dans un tel programme.

URL : Création d’un prototype de jeu sérieux sur la gestion des données de la recherche

DOI : https://doi.org/10.55790/journals/ressi.2023.e1093

Data Management Librarians Role in a Large Interdisciplinary Scientific Grant for PFAS Remediation: Considerations and Recommendations

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Authors : Jennifer Chaput, Renee Walsh

This article explores the conflicts, disparities, and inequalities experienced by two librarians when collaborating on a federal grant proposal. The authors discuss concerns related to time and salary expectations and the inequities that can occur during faculty and staff collaborations on research grants.

The bureaucratic structure and the job classifications of staff at academic institutions in addition to the contract limitations of non-faculty status librarian positions can hinder successful collaborations. The authors also describe data management needs that may occur when working with interdisciplinary research teams and detail the type of work that is included in writing a data management grant.

This article concludes with considerations and recommendations for other data librarians who may undertake similar projects with a focus on ways to create parity between faculty and staff collaborators.

URL : Data Management Librarians Role in a Large Interdisciplinary Scientific Grant for PFAS Remediation: Considerations and Recommendations

DOI : https://doi.org/10.7191/jeslib.616

Data Management Plans: Implications for Automated Analyses

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Authors : Ngoc-Minh Pham, Heather Moulaison-Sandy, Bradley Wade Bishop, Hannah Gunderman

Data management plans (DMPs) are an essential part of planning data-driven research projects and ensuring long-term access and use of research data and digital objects; however, as text-based documents, DMPs must be analyzed manually for conformance to funder requirements.

This study presents a comparison of DMPs evaluations for 21 funded projects using 1) an automated means of analysis to identify elements that align with best practices in support of open research initiatives and 2) a manually-applied scorecard measuring these same elements.

The automated analysis revealed that terms related to availability (90% of DMPs), metadata (86% of DMPs), and sharing (81% of DMPs) were reliably supplied. Manual analysis revealed 86% (n = 18) of funded DMPs were adequate, with strong discussions of data management personnel (average score: 2 out of 2), data sharing (average score 1.83 out of 2), and limitations to data sharing (average score: 1.65 out of 2).

This study reveals that the automated approach to DMP assessment yields less granular yet similar results to manual assessments of the DMPs that are more efficiently produced. Additional observations and recommendations are also presented to make data management planning exercises and automated analysis even more useful going forward.

URL : Data Management Plans: Implications for Automated Analyses

DOI : http://doi.org/10.5334/dsj-2023-002

RDM in a Decentralised University Ecosystem—A Case Study of the University of Cologne

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Authors : Constanze Curdt, Jens Dierkes, Sonja Kloppenburg

The University of Cologne (UoC) has historically grown in highly decentralised structures. This is reflected by a two-layered library structure as well as by a number of decentralised research data management (RDM) activities established on the faculty and research consortium level.

With the aim to foster networking, cooperation, and synergies between existing activities, a university-wide RDM will be established. A one-year feasibility study was commissioned by the Rectorate in 2016 and carried out by the department research management, library and computing centre.

One study outcome was the adoption of a university-wide research data guideline. Based on a comprehensive RDM service portfolio, measures were developed to put a central RDM into practice.

The challenges have been to find the right level of integration and adaptation of existing and established decentralised structures and to develop additional new structures and services.

We will report on first steps to map out central RDM practices at the UoC and to develop a structure of cooperation between loosely coupled information infrastructure actors. Central elements of this structure are a competence center, an RDM expert network, a forum for exchange about RDM and associated topics as well as the faculties with their decentralized, domain-specific RDM services.

The Cologne Competence Center for Research Data Management (C3RDM) was founded at the end of 2018 and is still in its development phase. It provides a one-stop entry point for all questions regarding RDM. T

he center itself provides basic and generic RDM services, such as training, consulting, and data publication support, and acts as a hub to the decentral experts, information infrastructure actors, and resources.

URL : RDM in a Decentralised University Ecosystem—A Case Study of the University of Cologne

DOI : http://doi.org/10.5334/dsj-2022-020

An iterative and interdisciplinary categorisation process towards FAIRer digital resources for sensitive life-sciences data

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Authors : Romain David, Christian Ohmann, Jan‑Willem Boiten, Mónica Cano Abadía, Florence Bietrix, Steve Canham, Maria Luisa Chiusano, Walter Dastrù, Arnaud Laroquette, Dario Longo, Michaela Th. Mayrhofer, Maria Panagiotopoulou, Audrey S. Richard, Sergey Goryanin, Pablo Emilio Verde

For life science infrastructures, sensitive data generate an additional layer of complexity. Cross-domain categorisation and discovery of digital resources related to sensitive data presents major interoperability challenges. To support this FAIRification process, a toolbox demonstrator aiming at support for discovery of digital objects related to sensitive data (e.g., regulations, guidelines, best practice, tools) has been developed.

The toolbox is based upon a categorisation system developed and harmonised across a cluster of 6 life science research infrastructures. Three different versions were built, tested by subsequent pilot studies, finally leading to a system with 7 main categories (sensitive data type, resource type, research field, data type, stage in data sharing life cycle, geographical scope, specific topics).

109 resources attached with the tags in pilot study 3 were used as the initial content for the toolbox demonstrator, a software tool allowing searching of digital objects linked to sensitive data with filtering based upon the categorisation system.

Important next steps are a broad evaluation of the usability and user-friendliness of the toolbox, extension to more resources, broader adoption by different life-science communities, and a long-term vision for maintenance and sustainability.

URL : An iterative and interdisciplinary categorisation process towards FAIRer digital resources for sensitive life-sciences data

DOI : https://doi.org/10.1038/s41598-022-25278-z

Putting FAIR principles in the context of research information: FAIRness for CRIS and CRIS for FAIRness

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Authors : Otmane Azeroual, Joachim Schöpfel, Janne Pölönen, Anastasija Nikiforova

Digitization in the research domain refers to the increasing integration and analysis of research information in the process of research data management. However, it is not clear whether it is used and, more importantly, whether the data are of sufficient quality, and value and knowledge could be extracted from them.

FAIR principles (Findability, Accessibility, Interoperability, Reusability) represent a promising asset to achieve this. Since their publication, they have rapidly proliferated and have become part of (inter-)national research funding programs.

A special feature of the FAIR principles is the emphasis on the legibility, readability, and understandability of data. At the same time, they pose a prerequisite for data for their reliability, trustworthiness, and quality. In this sense, the importance of applying FAIR principles to research information and respective systems such as Current Research Information Systems (CRIS), which is an underrepresented subject for research, is the subject of the paper.

Supporting the call for the need for a ”one-stop-shop and register-onceuse-many approach”, we argue that CRIS is a key component of the research infrastructure landscape, directly targeted and enabled by operational application and the promotion of FAIR principles.

We hypothesize that the improvement of FAIRness is a bidirectional process, where CRIS promotes FAIRness of data and infrastructures, and FAIR principles push further improvements to the underlying CRIS.

URL https://hal.archives-ouvertes.fr/hal-03836525

First Line Research Data Management for Life Sciences: a Case Study

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Authors : J. Paul van Schayck, Maarten Coonen

Modern life sciences studies depend on the collection, management and analysis of comprehensive datasets in what has become data-intensive research. Life science research is also characterised by having relatively small groups of researchers.

This combination of data-intensive research performed by a few people has led to an increasing bottleneck in research data management (RDM). Parallel to this, there has been an urgent call by initiatives like FAIR and Open Science to openly publish research data which has put additional pressure on improving the quality of RDM.

Here, we reflect on the lessons learnt by DataHub Maastricht, a RDM support group of the Maastricht University Medical Centre (MUMC+) in Maastricht, the Netherlands, in providing first-line RDM support for life sciences.

DataHub Maastricht operates with a small core team, and is complemented with disciplinary data stewards, many of whom have joint positions with DataHub and a research group. This organisational model helps creating shared knowledge between DataHub and the data stewards, including insights how to focus support on the most reusable datasets. This model has shown to be very beneficial given limited time and personnel.

We found that co-hosting tailored platforms for specific domains, reducing storage costs by implementing tiered storage and promoting cross-institutional collaboration through federated authentication were all effective features to stimulate researchers to initiate RDM.

Overall, utilising the expertise and communication channel of the embedded data stewards was also instrumental in our RDM success. Looking into the future, we foresee the need to further embed the role of data stewards into the lifeblood of the research organisation, along with policies on how to finance long-term storage of research data.

The latter, to remain feasible, needs to be combined with a further formalising of appraisal and reappraisal of archived research data.

URL : First Line Research Data Management for Life Sciences: a Case Study

DOI : https://doi.org/10.2218/ijdc.v16i1.761