In addition to the contents of this website, you will find below a selection of interesting resources on research data as well as other training courses and tools.
Other training materials
The e-Learning Platform for Research Data Management offers a range of 9 thematic modules to train in research data management.
This platform was developed as part of the "Train2Dacar" project.
DoRANum offers a distance learning system integrating various self-training resources on the management and sharing of research data.
Existing or created within the framework of the project, these resources offer several learning paths and methods to meet the expectations and uses of the target audiences: researchers, doctoral students and information professionals.
This service is offered by a network made up of Urfist and Inist-CNRS as well as representatives of the higher education and research community.
Developed by the University of Edinburgh, MANTRA is a free, unevaluated online course designed to provide the knowledge needed to understand and reflect on how to manage the digital data collected throughout the research cycle.
It was designed for students, early-career researchers and information professionals.
The course consists of eight online units and a set of offline data processing tutorials (downloadable). The aim is to enable users to become familiar with the key terminology and concepts in the field and to benefit from good practice in research data management.
The Consortium of European Social Science Data Archives offers a range of educational content on the management of social science research data, including :
- Data Management Expert guide: this guide offers a journey through the life cycle of research data, lasting approximately 15 hours. It has been designed by European experts to help social science researchers manage and make their research data findable, accessible, interoperable and reusable (FAIR).
- Webinars: the site offers recordings of webinars on various themes given in the past by Cessda.
- Train-the-Trainers Package: This kit contains various contents such as workshop plans, slides and exercises that trainers can use to develop and deliver research data management training for social scientists.
Developed in collaboration between the University of Cambridge and the Archaeology Data Service, DataTrain was designed to familiarise postgraduate archaeology students with good practices in research data management.
The course material consists of eight modules, each of which includes a powerpoint presentation with accompanying notes. The majority of the presentations end with a group discussion and/or written exercises.
The course material is freely available for re-use by trainers delivering basic research skills courses for archaeology students . The full course is designed to take place either as a four-hour half-day workshop or as a 2 x 2-hour course. The individual modules can also be integrated into courses in data management and basic research skills.
Led by different stakeholders in the UK, the Visual Arts Data Skills For Researchers (VADS4R) project has developed a Research Data Management (RDM) training programme tailored to the needs of early career researchers and postgraduate students in the visual arts.
The training material provided consists of 7 toolkits, each focusing on specific aspects of research data management for the visual arts.
The DLCM website is managed by the Swiss DLCM (Data Life Cycle Management) project team. It provides best practices, practical resources and news on this topic.
The website of the Digital Curation Centre (UK) provides expert advice and practical help in storing, managing, protecting and sharing digital research data.
Dataverse is an open source web application for sharing, preserving, quoting, exploring, and analyzing research data. A Dataverse repository is the installation of the software, which then hosts several dataverses. Each dataverse contains datasets, and each dataset contains descriptive metadata and data files (including documentation and code that accompanies the data).