The explosive deluge of digital data in all aspects of our society put their control in the heart of scientific, social and economic issues. Data can be heterogeneous, structured, large, distributed, high-speed continuous generated, etc. Then, new models of data representation, processing, access, use and protection are required to meet these issues.

Skills gathered in this group

To provide adequate answers, this research group aims to promote fertilization between different complementary areas of computer sciences related to data modeling, algorithmic, graph theory and combinatorics, data mining and statistical learning or languages and systems for databases.

Application fields , know-how , interface with other disciplines

• Smart cities and buildings
• Social-economic areas (manufacturing, social networks)
• Astronomical Data ( PetaSky )
• Sensor Networks, and possibly mobile robotics

Teams and researchers involved

30 permanent researchers compose the “Data Science” group. It brings together expertise from the data and problem modeling (graphs, algorithms, machine learning, declarative languages) and some system aspects (middleware, integration platforms, operational prototype), giving rise to its position as a major international research group over the entire processing line of data, including storage, analysis and querying.

The 32.5 permanent researchers involved in this group belong to the following teams :

• BD : 16
• DM2L : 9.5
• GOAL : 7

Keywords

• Theory of computation
  • Design and analysis of algorithms
    • Graph algorithms analysis
    • Distributed algorithms
    • Self-stabilizing graph algorithms
  • Theory and algorithms for application domains
    • Machine learning theory
      • Unsupervised learning and clustering
      • Bayesian analysis
      • Inductive inference
    • Database theory
      • Database query languages (principles)
      • Database constraints theory
      • Data structures and algorithms for data management
      • Theory of database privacy and security
• Mathematics of computing
  • Discrete mathematics
    • Graph theory
      • Graph matching
      • Graph parameters: colorings, domination, critical nodes, ...
      • Combinatorial games
      • Packing and decomposition
• Information systems
  • Data management systems
    • Database management system engines
      • Database query processing
      • Parallel and distributed DBMSs
      • Stream management
    • Query languages
      • Query languages for non-relational engines
  • Information systems applications
    • Data mining
      • Data cleaning
      • Association rules
      • Clustering
      • Data stream mining
    • Decision support systems
      • Data warehouses