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Scientific Data Management Certificate

186 CLASS
HOURS

Starting september 2021

for Students and lifelong learners

100 %
ONLINE

University certificate

Customisable modules

logo univ-montpellier
Logo-ISDM-couleur-300x153
Logo_MUSE_Original-300x150
logo investir l'avenir

Scientific Data Management Certificate

186 CLASS
HOURS

Starting september 2021

for students and lifelong learners

100%
ONLINE

logo univ-montpellier
Logo-ISDM-couleur-300x153
Logo_MUSE_Original-300x150
logo investir l'avenir

Certificate of Customary Law

Scientific Data Management Certificate

186 CLASS HOURS

starting september 2021

100% ONLINE

for students and lifelong learners

university certificate

customisable modules

Introducing the certificate

An exceptional multidisciplinary course in data science !

Montpellier’s Data Science Institute (ISDM) created the Scientific Data Management certificate as an answer to emerging scientific, technical and regulatory issues involving research data and open science.

You have the opportunity to enroll in 186 class hours in the use of scientific data. This exceptional course marshals instructors from the worlds of research and practice who will convey wide-ranging essential knowledge to you and share the methods, concepts and tools linked to new practices in research data management and openness.

Associated with ISDM and the University of Montpellier, the course is part of the CommonData research program, today the Platform of the Maison des Sciences de l’Homme SUD (MSH SUD). 

This online certification program, Europe’s first, addresses the need for new skills and practices that are today essential for research and innovative projects. A new profession is taking shape. Be ready to stand out!

Why take a course in scientific data management ?

To acquire the skills essential to meeting the new scientific and regulatory challenges of open science and to prepare yourself for the professions of the future.

The certificate-granting Scientific Data Management course, Europe’s first, is based on the scientific community’s observation that such training is needed. This need results from the implementation of open science policy, promoted by France’s 2018 National Plan for Open Science and the European Commission in 2012, as well as a concurrent demand to understand open data policy. Open science policy and open data are based on encouraging innovation via the development of the digital economy (an economy based on data). 

Data science marries computer science, math, and professional expertise to extract, explore, analyse and capitalise on masses of raw data, which are transformed into qualitative information used to solve problems or conduct innovative research.

The certificate, structured around standards developed by experts in the field, is a true asset for your professional career. Indeed, skills in scientific data management are sought after but graduates with such skills are extremely rare.

A scientific data administrator’s field of expertise is vast. The administrator must understand the meaning of open science and its challenges, as well as be an expert in the methods, concepts and tools related to new practices of managing and governing research data.

Your instructors will give you the tools to master the challenges of open science data and gain sought-after skills to apply in your daily work environment.

Course goals

Course goals

Goal 1

Understand the meaning of open science data and its scientific and regulatory challenges

Goal 3

Apply your new skills immediately thanks to practical exercises

Goal 2

Gain technical, legal and economic scientific data management skills

Goal 4

Stand out on the job market with your new, sought-after skills

Course goals

Educational approach

Doctrinal component

Get a grounding in the basics of scientific data management.

You’ll develop collaborative research skills, learn how to finance research on data collection and analysis, strategise how to build data science projects and understand the rules and regulations that apply to data.

Practical component

Understand the tools used to analyse scientific data and manage open science data.

This section of the course introduces scientific data analysis tools. These are the tools used to extract, contextualise, comb through, secure and protect data.

SDM Certificate by the numbers

0 h

of online classes and educational content.

0 %

online. Live and recorded classes.

0 %

flexible ! Our modules are customisable.

Les profils du DU SDM

Who are our students ?

Our 100% online Scientific Data Management certificate is highly flexible, making it well-suited to students and professionals. Students with a master’s degree and professionals wishing to get trained in the use of scientific data may apply.

Students with a master’s degree

Students with a master’s or advanced degree.

Doctoral students

Doctoral students and postdocs.

Project managers

Innovative project managers, whether at incubators or not.

Research professionals

Engineers, scholars, and researchers.

Quels profils ?

Our 100% online Scientific Data Management certificate is highly flexible, making it well-suited to students and professionals. Students with a master’s degree and professionals wishing to get trained in the use of scientific data may apply.

Students with a master’s degree

Students with a master’s or advanced degree.

Doctoral students

Doctoral students and postdocs.

Project managers

Innovative project managers, whether at incubators or not.

Research professionals

Engineers, scholars, and researchers.

Montpellier’s Data Science Institute

Follow ISDM

isdm-formation-sdm@umontpellier.fr

ISDM’s goal is to be a reference point uniting actors and trends in the worlds of data science and scientific data. Visit ISDM’s website.

ISDM’s goal is to bring together and guide the organisations and actors working to develop data science. It contributes to :
📌 defining a coordinated research data policy in open science and research data ;
📌
assisting research and project organisations requiring data skills ;
📌
circulating, hosting and training in data science ;
📌
implementing a digital services offer using the Meso@LR platform which proposes calculation, data, and Cloud services.

Objectifs de la formation

Les objectifs de la formation sont de comprendre les enjeux scientifiques et réglementaires de la Science ouverte des données et se former aux méthodes, techniques et outils pour se préparer aux nouveaux métiers. 

Objectif 1

Comprendre le sens et les enjeux scientifiques et réglementaires de la Science ouverte des données

Objectif 3

Appliquer vos nouvelles compétences dès la fin du DU grâce aux travaux pratiques

Objectif 2

Acquérir les compétences techniques, juridiques et économiques de la gestion des données scientifiques

Objectif 4

Se distinguer sur le marché de l’emploi grâce à de nouvelles compétences recherchées

Cette formation diplômante vous présentera l’environnement des données scientifiques sous deux angles :

→ Un angle doctrinal lié aux savoirs fondamentaux sur la gestion des données scientifiques. Cette partie de la formation vous permettra de comprendre l’environnement des données de la science.

Seront développés la recherche collaborative, le financement des recherches orientées vers la collecte et l’analyse des données, les stratégies de développement de projets de data science ainsi que les règles de gouvernance qui s’appliquent aux données.

→ Un angle pratique de «Scientific Data Manager » qui vise à maîtriser les outils d’analyse des données de la science ainsi que Gérer l’ouverture des données de la science.

Cette partie de la formation permet de donner les outils d’analyse des données de la science, c’est-à-dire les outils destinés à extraire, contextualiser, fouiller, sécuriser et protéger les données.

Ces deux angles d’approche seront organisés sous formes de modules qui représentent 186 heures de cours et de contenus pédagogiques en ligne.

Certains modules peuvent être suivis les uns indépendamment des autres. (Voir le programme)

Elle est ouverte en formation initiale et continue.

La formation est rattachée à l’Institut de la Science des Données de Montpellier et à l’Université de Montpellier. Elle est issue du programme de recherche CommonData, aujourd’hui Plateforme de la Maison des Sciences de l’Homme SUD.