On these pages you will find practical support to help you meet the 4 challenges of planning (DMP), collection and organization, storage and security, and archiving and sharing your data.
An introduction provides you with a better understanding of what research data management is, why it is important to be concerned about it in your research, who is responsible for it and what costs, if any, you should consider.
Research data management is "the part of the research process that deals with organisation and handling of research data, including data management planning, structured storing, description, curation, preservation and provision of metadata and complementary algorithms, code, software, and workflows, and compliance with internal, national and international privacy legislation." (OECD, 2021)
Research Data Management involves several stages, which together make up the research data lifecycle. Good research data management involves applying good practice at each stage of the data life cycle:
In 2015, 88% of UNIL researchers had never completed a Data Management Plan.
Find your Faculty's Data Steward
Bibliothèques de l'Université de Montréal, 2016
Directive 4.5
At UNIL, Directive 4.5 on research data processing and management defines the rules for managing research data, sets out the roles and responsibilities of the various parties involved and establishes the pricing principles for the use of the resources of the IT Service's Computing and Research Support Division (DCSR).
Useful guides on Research Data Management
- Data Management Expert Guide (CESSDA ERIC, en ligne)
- Guide rapide sur la gestion des données de recherche (HES-SO, 2023)
- Guide de bonnes pratiques sur la gestion des données de la recherche (l'Atelier Données – CNRS, 2023)
