  This paper presents identification of both network connected systems as well
as distributed systems governed by PDEs in the framework of distributed
optimization via the Alternating Direction Method of Multipliers. This approach
opens first the possibility to identify distributed models in a global manner
using all available data sequences and second the possibility for a distributed
implementation. The latter will make the application to large scale complex
systems possible. In addition to outlining a new large scale identification
method, illustrations are shown for identifying both network connected systems
and discretized PDEs.
