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Monday June 20, 2016 – Thursday June 23, 2016INP-ENSEEIHT2 Rue Charles Camichel, 31000 Toulouse, FranceOrganizers: A Quirin, M Grossetti, G Theraulaz, F Sedes, B Jouve, R Cazabet, L Beauguittehttp://www.isc-t.frAim and Scope:What are relevant parameters for describing spatio-temporal dynamics on or of networks? How to define a community of individuals in a network and characterize its dynamics? These questions are of great importance for social networks of course but also for other fields of application. Examples come for instance from transportation systems where new dynamic models arise in carpooling systems or in collaborative logistics. Another example is in the field of collective animal behaviour where models reproducing the construction dynamics of the networks provide a way to assess how each of the selected behavioral variables contributes to the emergent collective properties. In the economic domain, many economic markets, such as labor markets, involve outcomes that are determined not just by individual characteristics but also by network characteristics such as the structure of the professional contacts developed by the individuals in question. For human social networks, the way some individuals aggregate to constitute a community obeys rules that depend on the dynamic configuration of personal networks, though not only on this. In the case of biological networks, the characterization of temporal dynamics helps to decipher the evolutionary dynamics of multigenic gene families.Concerning spatialization, the bulk of spatialized relational data is constantly growing in contemporary societies (referring to economic relations, knowledge networks, various forms of social ties –including “social networks”, material and immaterial flows) and the study of spatial networks is a challenging field. Historians, on their side, are getting more and more interested in the reconstruction of spatial relations (travels, epistolary exchanges, social ties, etc.). When dealing with spatialized date, the issue of visualization of big spatialized networks (e.g. networks of scientists, interconnected rural places in Medieval France, global traffic flows) is central and is a way to switch from network graphs to efficient network maps. We shall also address the question of the dynamic building of spatialized networks. We may examine the impact of local changes (in terms of geographical, topological and/or network distances) on global properties of networks, which may give guides for model the organization of networks and even the rules of dynamics.Registration and program