Section outline

  • The scientific world has embrace digital technology in its research, publication and communication practices. It is now technically possible to open up science to the greatest number of people, by providing open access to publications and - as far as possible - to research data.

    This course introduces you to the challenges of Research Data Management and sharing (RDM) in the context of Open Science (OS).

    It was created within the framework of the Erasmus+ Oberred project in 2019. Other courses from the Oberred project are available on this platform.

    OBERRED project

    This course was carried out in the context of the Oberred project, co-funded by the Erasmus+ Programme of the European Union.

    Oberred is an acronym for Open Badge Ecosystem for the Recognition of Skills in Research Data Management and Sharing. The aim of the Oberred project is to create a practical guide that includes the technical specifics and issues of Open Badges, roles and skills related to RDM, and principles for the application of Open Badges to RDM.

    Find out more about the Oberred project here: http://oberred.eu/


    This course is open access!

    No account creation or registration is required, however you will only be able to browse it in read-only mode.
    To participate in the activities (exercises, forum...) and get the badge(s), you must register for the course.
    Register for the course

    For optimal use of this course, we recommend using the Google Chrome browser.

    • Course structure

      Lesson 1 : context and stakes of RDM

      This first lesson is an introduction to Research Data Management. It will enable you to grasp the context in which research data management takes place and give you an overall vision of the stakes involved in opening up and sharing such data.

      • Data and society
      • Data and science
      • Science and society : Covid-19 example
      • Open science and RDM
      • Evaluation1

      The second lesson will enable you to better understand the different steps of research data management, and to know the practices to be implemented and the tools to be used.

      • Understanding the data life cycle
      • FAIR principles
      • Data Management Plan (DMP)
      • Legal and ethical aspects
      • Metadata
      • Persistents identifiers
      • The 3 distincts stepsof data storage
      • Reuse and valorisation of data
      • Evaluation 2 


      Learning objectives

      This course should provide you with a good understanding of the context in which research data management and sharing takes place:

      • What are the issues and benefits of controlled data management? 
      • What concepts are related? 
      • How is data management organized and which actors are involved?

    • Auteur(s) / Formateur(s): Viêt Jeannaud, Nicolas Hochet, Yvette Lafosse, Pierrette Paillassard, Claire Sowinski, Coralie Wysoczynski, Marta Blaszczynska, Mateusz Franczak, Michel Roland, Tomasz Umerle, Beata Koper, Barbara Wachek, Lucas Ricroch
      Public cible: everyone
      Durée estimée: 1 week
      Prérequis: none
      Licence: CC BY-NC-SA
      Open badge: Yes
      Nombre d'inscrits: 3

    • Glossary