Overview

The exponential growth of data has urged the scientific community to consider developing efficient FAIR Research Data Management (RDM) strategies with an “Open Data” philosophy and implementing robust Data Management Plans (DMP) for research projects.
Adopting best RDM practices including FAIR principles (Findable, Accessible, Implementable, Reusable)1 not only enhances the value of your data by boosting visibility, reproducibility, and reuse, but also increases confidence in your findings2-4 and opens up opportunities for new collaborations.
These practices are mandated by funding agencies such as the Swiss National Science Foundation (SNFS) and Horizon Europe, as well as by leading publishing platforms.

This course, given by researchers and professionals involved in Research Data Management and in Data Management Plan preparation at ELIXIR-CH, SIB/Vital-IT and DSBU/FBM-UNIL/CHUV, will provide you with the knowledge and the tools 5 to generate robust data and excellent quality studies that follow the FAIR principles. This course will also provide you with effective support to build high quality DMP complying with the guidelines established by funding agencies.

Sources of information

1 Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). DOI: https://doi.org/10.1038/sdata.2016.18

2 Baker, M. 1,500 scientists lift the lid on reproducibility. Nature 533, 452–454 (2016). DOI: https://doi.org/10.1038/533452a

3 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. DOI: 10.1161/CIRCRESAHA.114.303819

4 Asher Mullard, “Preclinical cancer research suffers another reproducibility blow” Nature Reviews Drug Discovery 21, 89 (2022). DOI: https://doi.org/10.1038/d41573-022-00012-6

5 RDMkit: RDMkit The ELIXIR Research Data Management Kit.2022. https://rdmkit.elixir-europe.org/index.html.

Schedule

First day- 09:00-17:00 CET

At first, participants will be introduced to the notion of research reproducibility and to the need for a Data Management Plan (DMP) preparation, an evolving document reporting how the research data will be managed during and after a research project. You will learn best practices in FAIR Research Data Management (RDM) with a focus on data collection and data documentation.
During the exercises, participants will directly apply what they have learned.

In the afternoon, you will learn additional steps of the RDM cycle concerning ethics, legal, security issues, data preservation and data sharing, as well as an overview of the FAIR principles. During the exercises you will learn how to share your data on suitable repositories, such as Zenodo.

Second day- 09:00-17:00 CET

On the second day, participants will gain hands-on experience creating Data Management Plans (DMPs) tailored to their research using the effective and collaborative Data Stewardship Wizard (DSW) tool. They will also have the opportunity to share and receive feedback on their draft DMPs through group discussions. 

Audience

The course is addressed to PhD students, postdocs and researchers involved in life sciences and clinical research.

Learning objectives

At the end of the course you will be able to:
* Manage the main steps of your research rata using best practices and guidelines (RDM)
* Understand the FAIR guiding principles and Open Data foundations
* Understand the requirements of a Data Management Plan (DMP)
* Use the DSW tool to complete your own DMP

Prerequisites

Knowledge / competencies

To be involved in Life Sciences or clinical research.

Technical

You will need a laptop with a web browser installed.

Trainers

• Cécile Lebrand - Head of the Data Stewardship Biomed Unit (DSBU) at FBM UNIL- CHUV

• Vassilios Ioannidis - Lead Computational Biologist - FAIR specialist at SIB/Vital-IT and DSBU/FBM UNIL-CHUV

• Grégoire Rossier - Training Manager at SIB Training & Project Manager at SIB/Vital-IT

Application

While participants are registered on a first come, first served basis, exceptions may be made to ensure diversity and equity, which may increase the time before your registration is confirmed.

Deadline for cancellation is set to 09/10/2024.

You will be informed by email of your registration confirmation.

# Venue and time

This course will ONLY be held in person at the University of Lausanne (Metro M1 line, Sorge station). No online streaming will be offered.

It will start at 9:00 and end around 17:00 on each day.

Precise information will be provided to the participants before the course.

Additional information

Coordination: Valeria Di Cola, 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 [email protected].