6 Research Axis
2 Stakes & 8 Challenges
30 Research and Joint Research Units to develop digital agriculture in France and in Southern countries
56 PhD Grants
50 Labeled PhDs
150 Master Grants
18 Post-Doctoral Research Years
72 months of Hosting for High-Level Researchers
120 months of IT development for demonstrators based on thesis results

The general objective of #DigitAg is to build the scientific bricks required to foster the deployment of digital agriculture, based on an original interdisciplinary approach.

As suggested by the Convergence Lab name (“Human-centered Digital Agriculture”), the challenges to be addressed are related both to the comprehension of ICT introduction in, and interaction with, agriculture and farm management (economic, management and social issues) and to the design of new ICT-enabled devices, models, and tools for agricultural use, at any scale (technological, knowledge building and modelling issues). Both aspects are closely interlinked: a better understanding of ICT diffusion and actors will change the way researchers design new ICT-enabled services, whereas new models and easy-to-use ICT devices co-constructed with farmers and advisors pave the way for better dissemination. However, for now, they have been considered quite separately. This is the originality of #DigitAg to have appropriate communities interact to meet new Scientific and Technological objectives, poorly or never addressed in classical disciplinary and even multidisciplinary projects. Objectives are assigned to each axis bottleneck:

Axis 1: ICT and rural societies. The objective is to understand ICT influence on rural societies

  • To understand how ICT technologies contribute to improving management at farm level and territory governance.
  • To understand how ICT-enabled new services change the role of actors of the agriculture, incl. advisory services.

Axis 2:  Innovation in digital agriculture. Objective is to understand construction and legal issues of ICT-based innovation.

  • To understand how to successfully build technological and organisational innovation in “digital agriculture”
  • To address the legal and ethical issues of intellectual property of data and knowledge and consequences on value share

Axis 3: Sensors and data acquisition. Objective is to foster the development of suitable sensors and data acquisition systems,

  • To study and design sensors to address sensing bottlenecks e.g. field phenotyping, disease, plant & animal status.
  • To develop “frugal” data acquisition technologies based on use of smartphone devices and satellite images.

Axis 4: Information systems, data storage, transfer. The objective is:

  • To make progress in agricultural information system design, with the constraints of Big Data and interoperability

Axis 5 – Data Mining, Data Analysis and Knowledge Discovery. Objective is to design new data mining and visualisation methods, appropriate to agricultural data characteristics and users.

  • To design new data mining methods, appropriate to agricultural big data characteristics and preserving privacy;
  • To develop visual and interactive methods for data analysis, tailored for non-specialists.

Axis 6: Modelling production systems in smart agriculture. Objective is to explore new ways of model integration/qualification 

  • To make progress in genotype-to-phenotype modelling, by new data integration methods and knowledge injection;
  • To develop methods for integrating different types of information & knowledge (generated from data, experts, models…);
  • To make advances in quantification of uncertainty in agricultural models.