UNIVERSITY DEGREE: SCIENTIFIC DATA MANAGEMENT

Training structure
University of Montpellier
Language(s) of instruction
French

Presentation

The Scientific Data Management (SDM) training course aims to educate a wide audience about the challenges, practices, and tools involved in managing scientific research data.

Objectives

The aim of the course is to raise awareness and provide training in open science techniques, as well as to explain their significance and implications. The program offers a broad range of courses in computer science applied to data management, data engineering (anonymization, storage, archiving), project engineering, intellectual property and digital law, etc. For this reason, the program also offers courses in knowledge and know-how (practical work).

This is a degree program leading to a university diploma (DU). However, some modules can be taken independently of each other. In this case, the program will only lead to a certificate and not a degree.

It is open for initial and continuing education.

The training program is affiliated withthe Montpellier Institute of Data Science andthe University of Montpellier. It originated from the CommonData research program, now known as the Plateforme de la Maison des Sciences de l’Homme SUD.

Laurent Burnel, class of 2020/2021

"I work at INRAE, and I am currently retraining for a role supporting groups in the transition to open data within my institute. The opening up of research data has and will continue to have a significant impact on research practices throughout the data lifecycle, and therefore concerns all research staff.

I was looking for a fairly broad course on research data management, and there aren't many available, which is why this university diploma was a real opportunity for me. It offers a comprehensive overview of the different aspects of open data, and the lecturers are open data practitioners who are experts in their field. The courses offered take both a theoretical approach, which is necessary, and a practical approach, which is well illustrated by the speakers' experience."

Véronique Arnal, class of 2020/2021

"The SDM university diploma is a training program that teaches you which research data to make available to the scientific community and which to protect, how to make data FAIR (findable, accessible, interoperable, and reusable), how to extract knowledge from it, and finally, how to manage it strategically in the short, medium, and long term! It provides you with a range of tools and enables you to raise awareness and advise researchers on open science policy! In short, you become a 'data steward'."

Training summary

	Diploma	University degree, 5 years of higher education
	Entry level	Master's degree
	Required entry level	No
	Distance learning	Mandatory
	Start date of the training	September 20, 2021
	Registration start date	April 1, 2022
	Registration deadline	Feb. 3, 2023
	Location(s)	Montpellier

Place of instruction

Other contacts

Agnès Robin, educational manager for the training program: agnes.robin @ umontpellier.fr

Hélène Leay, training coordinator: veak-chhanny.leay @ umontpellier.fr

Affiliated with the Montpellier Institute of Science: isdm-formation-sdm @ umontpellier.fr

DU Scientific Data Management

Organization

Knowledge assessment

Report to be submitted, followed by a defense at the end of the year for students who wish to graduate

Program

Understanding the data environment in science

The first part of the training course provides an understanding of the scientific data environment:

What is collaborative research?
How can research focused on data collection and analysis be financed?
What are the strategies for developing data science projects?
What legal and/or governance rules apply to data?

3 modules for part 1

Mastering scientific data analysis tools

The second part of the training program focuses on mastering scientific data analysis tools, i.e., tools designed to extract, contextualize, search, secure, and protect data.

5 modules for part 2

Managing the opening up of scientific data

The third part focuses on training in open science data. It involves learning how to share and publish data, but also how to store and archive it securely so that it can potentially be reused and/or exploited.

4 modules for part 3

Admission requirements

Motivation to demonstrate
Minimum Master's degree

Applications are reviewed by the teaching team.

Initial and continuing education
Doctoral students: participation in the training will result in a certificate for the corresponding number of hours. However, you must first ensure that the hours of this training will be taken into account by your doctoral school. Similarly, enrollment in doctoral training does not equate to enrollment in the university diploma program. The two enrollments are separate.

Teaching methods

Distance learning

Mandatory attendance at all live sessions

You can choose which modules to take. However, please note that some modules are interdependent.

Researchers
Faculty members
Postdoctoral researchers
Doctoral students
Engineers
Innovative project leaders (incubated or not)
Master's students

Expected results

Diploma validation

Mandatory attendance: completion of all training modules
defense: in the form of a presentation of a scientific data management project before a jury
have obtained a score of ≥ 10/20 for the preparation and presentation of the project

Certificate of training completion

Issued upon request to individuals who have completed at least five modules, bearing in mind that certain modules are prerequisites for other modules.

UNIVERSITY DEGREE: SCIENTIFIC DATA MANAGEMENT

Training structure

Language(s) of instruction