WP1 : Data Science for Earth, Space and Environmental Sciences

This action will exploit the huge potential of applying modern data analytics in ESES. It will overcome disciplinary and technical barriers and provide new statistical and computational approaches, in particular for data in astrophysics to better characterize exoplanets, in oceanography to better infer vertical exchange in the ocean, and in ecology to reconstruct interaction networks between species.

WP2 : Data Science for Life Sciences

Life and health sciences are changing rapidly: new technologies provide large-scale individual data (“omics” data) that can be related to health-related outcomes and medical imaging data. Identifying predisposition factors for disease and making predictions about health is a tremendous challenge for data scientists that we will address by conceiving original data science methods, algorithms, and software to relate omics data to health-related traits.

WP3 : Massive and Rich Data for Humanities

This project aspires to re-dimension research in the humanities fields, from small isolated corpora of rich data to a large interconnected corpus of rich data. It will cover scientific problems ranging from the massive production of rich data, to operating, querying and visualizing  voluminous data, through perennial preservation of the data and metadata, thus questioning methodology in humanity research.

WP4 : Data Science, Social Media and Social Sciences

New data sources coming from the web and social media are made available to analyze social structures in innovative ways. Social media have recently become a promising observatory of society. Social scientists and computer scientists will deliver new machine learning methodologies to provide a better understanding of the dynamics of opinions, careers and urban structures.

WP5 : Data Governance, Data Protection and Privacy

We will analyze, in a multi-disciplinary perspective, why and how specific forms of data governance emerge as well as the consequences on the interaction between the state, the market and society. We will focus on the challenges raised by the collection and use of data for privacy, on the data subjects’ rights and on the obligations of data controllers and processors. We will propose Privacy Impact/Risk assessments methodology and software. A case study will focus on medical and health data and make recommendations on how they should be collected and processed.