Workshop: “From Bench to FAIR Data: Practical Approaches to Research Data Management in Life Science”

FBM PhD course open to Postdoctoral researchers and data managers

Co-organized by the DSBU, University Center for Primary Care and Public  and the FBM Doctoral School

Tuesday 24 November & Wednesday 25 Novembe 2026
 – In-person sessions

From 9:15 to 17:30

Epalinges – bâtiment SE-C
Rte de la Corniche 7, 1066 Lausanne
Room SEC/01/006 (Metro M2 line, Croisette station)

Course Structure

The course is organized into three sessions: two full-day in-person workshops (Days 1 and 2)

The in-person sessions are divided into four modules that combine theory with practical exercises using real data examples and institutional tools.

Participants will work together to cover the organization and management of research data, the creation of clear documentation and standardized metadata using institutional tools, and the principles of FAIR data sharing and long-term preservation. and consolidated during the final in-person sessions

Overview

The exponential growth of research data in life sciences and clinical research has made it crucial to implement robust Research Data Management (RDM) strategies based on Open Research Data practices.

Applying the FAIR principles (Findable, Accessible, Interoperable and Reusable) brings major benefits: improving data visibility, reproducibility, reusability, and credibility, while enabling new scientific collaborations and research questions.

This two-day theoretical and hands-on workshop, co-organized by the Data Stewardship BioMed Unit (DSBU) and the FBM Doctoral School, offers a practical and comprehensive introduction to RDM and the FAIR principles in the context of life sciences and clinical research.

Through a mix of lectures and guided exercises, participants will learn to manage their data according to FAIR and reproducible research standards and to use institutional and open-source tools to support these practices.

Target Audience

This workshop is reserved for members of the Faculty of Biology and Medicine (FBM) at the University of Lausanne (UNIL) and the University Hospital of Lausanne (CHUV).

  • PhD students in life sciences or pre-clinical research handling digital research data
  • Postdoctoral researchers and data managers, including those fulfilling data management roles in research laboratories
  • For PIs, shorter and tailored training sessions are organized separately for their research groups, focusing on the specific data types and research themes of individual groups. PIs interested in customized workshops related to their own research are encouraged to contact us.

Learning Outcomes

By the end of the course, participants will have acquired both theoretical and practical skills to implement FAIR and reproducible Research Data Management (RDM) practices throughout the research lifecycle.

Participants will learn to:

  • Organize research data efficiently and select appropriate file formats for FAIR sharing and long-term preservation
  • Develop and update Data Management Plans (DMPs)
  • Document datasets with README files and metadata using DataSquid@DSBU for semi-automated data documentation
  • Integrate and harmonize metadata across systems and deposit datasets in FAIR-compliant repositories (e.g., FBM Zenodo Community, ENA for sequencing data or BIA for imaging data)
  • Understand the principles of long-term data preservation via tape-based archiving solutions

Course Structure

Each module combines a theoretical introduction with hands-on exercises using real data examples and institutional tools.

The course is structured over four main sessions with two in person session (Days 1 and 3).

Day 1 – Tuesday, 24 November 2026 (Full day from 9:15 to 17:30, in person)

Module I: Data Types & Organization

Participants will be introduced to best practices in data and file management across the research lifecycle.

Topics include:

  • Data entry validation, folder structure, file naming and file formats
  • Selecting sustainable file formats for sharing and preservation
  • Creating personalized DMP.

Module II: Data Documentation

During this module, participants will enhance their data management, structuration and documentation skills through metadata and README files, using tools to facilitate efficient data organization, storage, retrieval, and sharing.

Participants will learn how to:

  • apply metadata standards
  • manage their research data using DataSquid@DSBU 
  • create structured README files using DataSquid@DSBU 

Students will learn how to use DataSquid to structure and document their own research data during two hands-on sessions: one at the end of the first day and a second on the following day. They will apply the concepts introduced during the course directly to their own datasets and research workflows.

Day 3 – Wednesday, 25 November 2025 (Full day from 9:15 to 17:30, in person)

Module III: Metadata Integration and FAIR Repositories

This module focuses on the practical application of FAIR data-sharing workflows, from metadata integration and data documentation to dataset deposition, publication, and long-term preservation.

Through demonstrations and hands-on exercises, participants will learn how to:

  • Prepare datasets and their documentation for secure long-term preservation through tape-based archiving, ensuring that research data remain preserved, secure, and accessible over time.
  • This module focuses on the practical application of FAIR data-sharing workflows, from metadata integration and documentation to dataset deposition and publication.
  • Identify the most appropriate repository for their research data and understand its deposition requirements using FAIRShare Explorer.
  • Use DataSquid to prepare and structure the metadata captured and documented throughout the research process for data sharing, publication, and long-term preservation.
  • Explore DataSquid’s integration with UNIL’s DCSR infrastructure, with a practical focus on documenting data for both short-term storage and long-term storage (LTS).

Module IV – Publication of biomedical Datasets

The Life science module will provide deepen practices of FAIR data sharing within generalist and specialized repositories.

Participants will gain hands-on experience in:

  • Upload, describe, and publish datasets on the generalist repository such as FBM Zenodo Community,
  • Reuse, copyright, and license data.Depositing sequencing and imaging data in repositories such as ENA and BioImage Archive, using either participants’ own data or a provided dataset

Evaluation and Credits for PhD Students

1 ECTS credit awarded upon:

  • Active participation during the workshop
  • Short presentation of practical outcomes
  • Completion of the independent work (no final written exam)

Teachers

  • Cécile Lebrand, PhD, Head of the DSBU, FBM UNIL–CHUV
  • Vassilios Ioannidis, PhD, Lead Computational Biologist – FAIR Data Specialist, DSBU, FBM UNIL–CHUV
  • Florian Mauffrey, PhD, Biomedical Data Scientist, DSBU, FBM UNIL–CHUV

Requirements

  • Participants must bring their own laptop.
  • They should also come with a dataset from their own research that needs to be documented, as well as a clear understanding of the instruments, software, and data acquisition workflows used in their laboratory.
  • This will allow participants to apply the concepts and tools presented during the workshop directly to their own research context.

References & Resources

Registration

Registration via the DSBU contact form

Participation is free of charge.