Head: FabSpace 2.0 is an innovation network which focus on the exploitation of geospatial data across universities. The objective of FabSpace 2.0 is to bring together, around a common project, people with a variety of skills (industry players, university researchers, public administrations and citizens). Like a FabLab, FabSpace has a place where people can meet and co-create together, in a multidisciplinary approach. The FabSpace platform facilitates access to open data,
Principal Investigator : Context During the Spring 2020 lockdown, the CNRS Institute of information sciences and their interactions (InS2I) via its DAS Mokrane Bouzeghoub mobilized six teams from CNRS UMRs on COVID-related issues19 involving data science and information retrieval. INS2I has linked the IRIS team with epidemiologists from CRESS (UMR 1153 INSERM). The latter carry out a real-time review of the scientific literature (living systematic review) of the COVID19 and
Pascale ZARATÉ, du département Intelligence Artificielle – Equipe ADRIA, était professeur invitée à Nanjing University of Aeronotics and Astraunotics (NUAA), Chine, du 15 au 27 Novembre 2019. Elle a établi une collaboration avec la Professeure Haiyan Xu du College of Economics and Management. Durant ce séjour, elle a présenté ses travaux dans diverses universités. Un accord de collaboration devrait être signé. Les visites au professeur Yuming Zhu de la NorthWestern
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Heads : and The Technology Enhanced Learning (TEL) ( also called e-Learning) field, whose main aim is to , use digital technologies for enhancing education, has been a growing area in the past decade. e-Learning is nowadays adopted in almost all training institutions, in both the public or private sector, to support and strengthen traditional teaching and learning practices, but also to propose new innovative practices that cannot be implemented
Head: Social media constitute a field of application, experiment, a support for the formalization and a source of scientific and technological issues we are far from reaching the limits. Managing, modeling, analyzing, mining and eliciting such a digital ecosystem have been highlighted by various contributions of our teams. From the analysis of the dynamics of the social networks, for example for the detection of communities, are studied the processes of
