Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
XML PDF e-pub
PDF e-Pub

Section: Partnerships and Cooperations

National Initiatives


#DigitAg: Digital agriculture

Participants : Alexandre Termier, Véronique Masson, Christine Largouët, Anne-Isabelle Graux.

#DigitAg is a “Convergence Institute” dedicated to the increasing importance of digital techniques in agriculture. Its goal is twofold: first, make innovative research on the use of digital techniques in agriculture in order to improve competitiveness, preserve environment, and offer correct living conditions to farmers. Second, through education prepare future farmers and agricultural policy makers to successfully exploit such technology.

While #DigitAg is based on Montpellier, Rennes is a satellite of the institute focused on cattle farming. Lacodam is involved in the “data mining” challenge of the institute, that A. Termier co-leads. He is also the representative of Inria in the steering comittee of the institute.

The interest for the team is to design novel methods to analyze and represent agricultural data, which are challenging because they are both heterogeneous and multi-scale (both spatial and temporal).

National Platforms

PEPS : Pharmaco-epidemiology for Health Products

Participants : Yann Dauxais, Thomas Guyet, Véronique Masson, René Quiniou, Alexandre Termier.

The PEPS project (Pharmaco-epidemiology des Produits de Santé) is funded by ANSM (national agency for health security). The project leader is E. Oger from the clinical investigation center CIC-1414 INSERM/CHU Rennes. The other partners located in Rennes are the Institute of Research and Technology (IRT) B<>Com, EHESP and the LTSI. The project started in january 2015 and is funded for 4 years.

The PEPS project has two parts: the clinical studies and a research program dedicated to the development of innovative tools for pharmaco-epidemiological studies with medico-administrative databases.

Our contribution to this project will be to propose pattern mining algorithm and reasoning techniques to analyse the typical care pathways of specific groups of insured patients.