In an increasingly digital world, large volumes of complex data (big data) are now central to any decision-making process.
Organizing this data to efficiently query it and envisioning new programming paradigms is a fundamental step in order to extract knowledge from this data, a crucial precondition in data science.
The goal of studies conducted at Dauphine is to design, examine, and analyze, on an experimental basis, techniques for the management and analysis of semi-structured data, with a particular focus on web data and graph-structured data.
The research is structured around the following areas:
- Retrieval of aggregate information on workflows
- Secure, efficient processing of massive amounts of graphical data
- Big data integration via crowdsourcing
- Discovery, composition, and reliable execution of web services
- Aggregated search of data and services for linked data
Dario Colazzo, Daniela Grigori, Khalid Belhajjame, Maud Manouvrier, Joyce Elhaddad, Elsa Negre, Marta Rukoz, and Michel Zamfiroiu