BACKGROUND

The mission of STO is to conduct and promote co-operative research and information exchange. STO consists of a three level organization: the Science and Technology Board (STB), the Panels and the Technical Teams. The Information Systems Technology (IST) Panel is one of the seven Panels under the STB.

The Mission of the Information Systems Technology (IST) Panel is to advance and exchange appropriate technologies in order to provide timely, affordable, dependable, secure and relevant information and to improve C3I systems including special focus on Interoperability and Cyber Security

THEME

For NATO’s crisis reaction and peace-keeping missions, information dominance has been a proven key element for preventing open conflicts. To this end, vast amounts of “hard” and “soft” data have to be exploited and intelligently “fused” to usable pieces of operationally relevant information. In this process, a variety of data from very diverse sources has to be considered: distributed networks of heterogeneous sensors, networking data base systems, providing context and background information, and human observers delivering language-encoded messages via various channels. Only on a sound informational basis can reasonable and morally justifiable decisions be made. Since NATO’s success story of preserving peace has been depending to a large extent on NATO’s broad societal acceptance, strict boundary conditions defined by fundamental human rights are particularly relevant to future missions.

TOPICS TO BE COVERED

The Lecture Series Team will present, in a tutorial fashion, core methodologies and algorithms that solve the various aspects of “hard” and “soft” information fusion. The lectures will address sensor and textual data in its physical and environmental context (typically determined while operating the system), partially known context (often described by statistical models), and language-encoded context. Often these categories do not appear isolated from each other. Even legal and socio-political constraints are context information that must be properly taken into account. The lectures will extend the highly successful paradigm of sensor data fusion to broader applications. On the other hand, computer-linguistic approaches enable fusion of language-encoded information that was out of reach before.