Information and Data Fusion is a discipline that provides methods and techniques to build Observe-Orient-Decide-Act (OODA) capabilities for various applications. There are many ways in which these methods and techniques can be chosen to provide capabilities in each phase of the OODA decision making cycle, and there are different fusion architectures, i.e., ways these methods and techniques can be applied, grouped and integrated. How one chooses the most appropriate set of methods, techniques and fusion architecture for an application depends on a number of factors. Additional factors have to be considered in the case when decision making is performed through a collaboration of a number of fusion centres on a network, defined as Distributed Data Fusion, in the context of this lecture. This lecture describes the choices for fusion architectures, the factors leading to the selection of a fusion architecture, and proposes a model to help make these choices in the case of distributed data fusion.