Introduction to FAIR Research Data Management & Data Management Plan

We are sorry but this course is oversubscribed, with a long waiting list.

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Overview

The huge amount of generated research data has urged the scientific community to consider developing efficient FAIR Research Data Management Strategies with an “Open Data” philosophy and implementing robust Data Management Plans (DMP) for research projects. This need is also reflected in the requirements of funding agencies, amongst which the Swiss National Science Foundation (SNFS), Horizon Europe, and publishing platforms. Making research data FAIR - Findable, Accessible, Interoperable and Reusable ¹ - provides many benefits, including to increase the visibility and to improve the reproducibility, reuse, and the confidence towards the data ^2-4, as well as to enable new research questions and collaborations.

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 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 published data on adapted repositories, such as Zenodo.

Second day- 09:00-17:00 CET

On the second day, participants will learn how to fill a DMP corresponding to their own research using the “Data Stewardship Wizard” tool. Participants will also be able to present and discuss their draft DMPs with the group. 

Audience

The course is addressed to post-graduate 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 FAIR Data Management principles in general.

Learning objectives

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

• Understand the requirements of a Data Management Plan (DMP)
• Manage the main steps of your research rata using good practices and guidelines (RDM)
• Understand the FAIR guiding principles and Open Data foundations
• Use the DSW tool to complete your own DMP

Prerequisites

Knowledge / competencies

To be involved in Life Sciences research.

Technical

You will need a laptop with a web browser installed.

Trainers

• Cécile Lebrand - Head of Open Science service at FBM UNIL/CHUV; Data Steward at UNIRIS

• Vassilios Ioannidis - Lead Computational Biologist at SIB/Vital-IT; Data Steward – FAIR Specialist at UNIRIS

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

Application

This course is free of charges. It is partially sponsored by ELIXIR-CONVERGE. 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 15/06/2023.

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 training@sib.swiss.

This SIB course is organized in collaboration with

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