Complex systems are characterized by the presence of intricate interactions between their heterogeneous parts, and an overall behavior which can not be easily explain by the properties of these individual components. For such systems, it is therefore particularly interesting to focus on how information flows between these parts, in terms of dynamical and statistical properties. This flow may represent data on a communication network, financial market interactions, gene interactions, or even a disease spreading within a population.

Due to their complexity, the analysis of such systems is not trivial. They are associated with large datasets, which require advanced techniques. Similarly, prediction implies the development of refined models and simulation tools. Such developments are often only possible high-performance computing. Cloud computing also emerges as a suitable option in some cases, and several presentations at this workshop will look at these alternatives.

Any submission whose content is relevant to the areas of data analysis, computational modeling, networks and complex systems will be considered, but any submission whose subject matter is related to one of the following topics will be particularly welcome:

Analysis and modeling of large-scale networks (e.g. communication networks, social networks)
- Modeling and design of complex networks
- Tools and metrics for large networks
- Information diffusion in communication networks

Towards e-Health: biomedical and social systems
- Network approaches in genetics and epigenetics
- Personalized medicine
- Population studies: alert systems, epidemic modeling, etc.
- Big (bio-)data: biological and medical data analysis

New solutions for computationally-intensive problems
- HPC for data analytics
- Cloud computing
- Pre-computation
- Optimization approaches to complex systems

Tools and Case-studies
- Applications, experience reports and case studies in data analytics
- Applications, experience reports and case studies in computational modeling
- Tools for large-scale data analysis