International audienceInformation overload and complexity are core problems to most organizations of today. The advances in networking capabilities have created the conditions of complexity by enabling richer, real-time interactions between and among individuals, objects, systems and organizations. Fusion of Information and Analytics Technologies (FIAT) are key enablers for the design of current and future decision support systems to support prognosis, diagnosis, and prescriptive tasks in such complex environments. Hundreds of methods and technologies exist, and several books have been dedicated to either analytics or information fusion so far. However, very few have discussed the methodological aspects and the need of integrating frameworks for these techniques coming from multiple disciplines. This paper presents a discussion of potential integrating frameworks as well as the development of a computational model to evolve FIAT-based systems capable of meeting the challenges of complex environments such as in Big Data and Internet of Things (IoT)
