UNIVERSITY DIPLOMA: SCIENTIFIC DATA MANAGEMENT

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

Presentation

The aim of the "Scientific Data Management" (SDM) or "Gestion des données scientifiques" (GDS) course is to train a wide audience in the issues, practices and tools involved in managing scientific research data.

Objectives

The aim of the training program is to raise awareness and provide training in open science techniques, as well as to explain the meaning and issues involved. The course therefore offers a wide range of courses in computer science applied to data management, data engineering (anonymization, storage, archiving), project engineering, intellectual property and digital law, and more. For this reason, the course also includes practical work in the areas of knowledge and know-how.

This is a University Diploma (DU) type course. However, some modules can be taken independently. In this case, the training will only lead to certification, not a diploma.

It is open to both initial and continuing training.

The course is attached to theMontpellier Data Science Institute and theUniversity of Montpellier. It grew out of the CommonData research program, now the Plateforme de la Maison des Sciences de l'Homme SUD.

Laurent Burnel, class of 2020/2021

"I work at INRAE, and I'm currently undergoing professional retraining, preparing myself for a role supporting groups towards open data, within my institute . The opening up of research data has and will increasingly have a strong impact on research practices, throughout the data life cycle, and therefore concerns all research staff.

I was looking for a wide-ranging course on research data management, and there aren't many available, so this DU was a real opportunity for me. It offers a complete panorama of the different facets of open data, and the lecturers are practitioners of open data, experts in their field. The courses offered are both in a theoretical approach, which is necessary, but also practical, well illustrated by the experience of the lecturers."

Véronique Arnal, class of 2020/2021

"The DU SDM is training in how to know what research data to open up to the scientific community or, conversely, how to protect it, 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! This is the perfect way to acquire a wide range of tools, and to raise awareness and advise researchers on open science policy! In short, become a "Data steward"."

Training summary

	Diploma	University degree level bac + 5
	Input level	BAC +5
	Mandatory entry level	No
	Distance learning	Mandatory
	Training start date	Sept. 20, 2021
	Registration start date	Apr. 1, 2022
	Registration end date	Feb. 3, 2023
	Location(s)	Montpellier

Teaching location

Other contacts

(isdm-formation-sdm @ umontpellier.fr)Agnès Robin, Training Manager: agnes.robin @ umontpellier.fr (agnes.robin @ umontpellier.fr)

Hélène Leay, Training Coordinator : veak-chhanny.leay @ umontpellier.fr (veak-chhanny.leay @ umontpellier.fr)

Attached to the Montpellier Institute of Science : isdm-formation-sdm @ umontpellier.fr (isdm-formation-sdm @ umontpellier.fr)

DU Scientific Data Management

Organization

Knowledge control

Report due, followed by an oral presentation at the end of the year for students wishing to graduate.

Program

Understanding the data environment of science

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

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

3 modules for part 1

Master the tools of scientific data analysis

The second part of the course provides training in data analysis tools for science, i.e. tools for extracting, contextualizing, mining, securing and protecting data.

5 modules for part 2

Managing the opening up of scientific data

The third part proposes training in opening up scientific data. This involves learning how to share, publish, store and archive data securely, so that it can be reused and/or valorized.

4 modules for part 3

Access conditions

Motivation to demonstrate
Minimum Master's level

Applications are submitted to the educational team for review.

Initial and continuing training
Doctoral student: participation in the training course will give rise to a certificate for the corresponding number of hours. However, you must first make sure that the hours spent on the course will be taken into account by your Doctoral School. Similarly, enrolment in the doctoral training program is not the same as enrolment in the DU. The two registrations are separate.

Teaching methods

Distance learning

Mandatory attendance at all live sessions

Choice of modules. Please note, however, that some modules are interdependent.

Researchers
Teacher-researchers
Post-docs
Doctoral students
Engineers
Innovative projects (incubated or not)
Master's students

Expected results

Diploma validation

compulsory attendance: completion of all training modules
defense: in the form of a presentation of a scientific data management project to a panel of judges
have obtained a mark ≥ 10/20 for project preparation and presentation

Training follow-up certificate

issued on request, for people who have completed a minimum of 5 modules, bearing in mind that some modules are essential prerequisites for others.

UNIVERSITY DIPLOMA: SCIENTIFIC DATA MANAGEMENT

Training structure

Language(s) of instruction