Research Data Managment and Data Management Plan

Date 28 - 29 October 2021
Speaker(s) Cécile Lebrand, Grégoire Rossier, Vassilios Ioannidis
Cancellation deadline 12 Oct 2021
City Lausanne


Recent studies have shown that worldwide, between 51% and 89% of published life sciences research is not reproducible, with consequent losses estimated at around $100 billions/year in biomedical research (Chalmers et al., 2009; Freedman et al., 2015; Begley and Ioannidis, 2015). In particular, these studies have made clear that the research data associated with a publication are fundamental to validate the published analyses and results. Many causes contribute to this lack of reproducibility in life science studies such as a lack of rigor in data management and analysis. This extensive problem related to improper research management has urged scientists to consider developing efficient Data Management Plans (DMP) for their research projects, a need that is also reflected in the requirements of funding agencies, amongst which the Swiss National Science Foundation (SNFS) and Horizon 2020.

This course, given by researchers and professionals involved in Big Data management at SIB/Vital-IT as well as in Data Management Plan preparation at UNIL/CHUV, will provide you with effective support to produce high quality DMP complying with the guidelines established by funding agencies. Importantly, it will provide you with tools to generate robust data and excellent quality studies that are reproducible and reusable.

Sources of information

  • Begley, C G, and Ioannidis, J. PA. “Reproducibility in science improving the standard for basic and preclinical research.” Circulation research. 2015; 116.1: 116-126.
  • Chalmers I, Glasziou P. Avoidable Waste in the Production and Reporting of Research Evidence. Lancet. 2009; 374(9683): 86–89.
  • Freedman LP, Cockburn IM, Simcoe TS. The Economics of Reproducibility in Preclinical Research. PLoS Biol. 2015;13(6): e1002165.


More information soon...


The course is addressed to postgraduate students and researchers who plan to apply for SNFS funds and want to be trained on how to efficiently complete the Data Management Plan form. At the same time, this course aims at educating the participants on Data Management principles in general.

Learning objectives

At the end of the course you will be able to:

  • put in place a DMP (data management plan) which fulfills the requirements of the funding agencies such as the SNFS and H2020, which require a DMP to be put in place
  • manage in detail your research data, specifying how your data will be analysed, organised, stored, secured and shared
  • specify the type of data that is going to be created and shared
  • indicate the process to be followed in respect of the budget, intellectual property, and monitoring
  • use the “SIB/Vital-IT DMP Canvas Generator tool” to make your own DMP template.


Knowledge / competencies

To be involved in Life Sciences research.


You will need a laptop with a web browser installed.


  • Cécile Lebrand – Open Science advocate and information specialist Bibliothèque Universitaire de Médecine, CHUV

  • Vassilios Ioannidis – SIB/Vital-IT Competence Center & Core-IT, SIB Swiss Institute of Bioinformatics

  • Grégoire Rossier - SIB/Vital-IT Competence Center & SIB Training, SIB Swiss Institute of Bioinformatics


Application is not open yet.

Venue and time

This course will take place at the University of Lausanne.

It will start at 09:00 CET and end around 17:00 CET. Precise information will be provided to the participants in due time.

Additional information

Coordination: Diana Marek, SIB Training Group

You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.

Please note that participation in SIB courses is subject to our general conditions.

SIB abides by the ELIXIR Code of Conduct. Participants of SIB courses are also required to abide by the same code.

For more information, please contact

drawing drawing ELIXIR-CONVERGE is funded by the European Commission within the Research Infrastructures programme of Horizon 2020