Distributed signals and data will be of great importance to our future daily life. The application of ubiquitous networked sensors, processing units, and distributed data sets will enhance the understanding of our world and its sustainable use. In this context, massive amounts of data have to be turned into concise and useful information, which demands groundbreaking new science at the intersection of mathematics, signal and information processing, communications theory, and scientific computing.

The network aims at developing new theories, algorithms, and implementations that enable the extraction, compression, transmission, and storage of information in large-scale distributed data sets. The focus is on distributed architectures which can be designed to be fault tolerant and scalable. The concepts and methods that will result from this basic research will be applicable to sensor and communication networks, distributed systems, cooperative wireless communications, machine learning, embedded system design, medicine, and molecular biology.

The following key technologies are investigated:

• Signal and Information Representation
• Statistical Inference
• Nonlinear Dynamics and Machine Learning
• Information Networks
• Wireless Communications
• Distributed Computing and Information Processing
• Design Methodology

The network spans a consortium of groups from Vienna University of Technology, Vienna Telecommunications Research FTW, University of Vienna, and Graz University of Technology.