Developing evidence and understanding concerning Global Systems and related policies is rapidly becoming a vital challenge for modern societies. It is being tackled by the newly-emerged scientific domain of Global Systems Science (GSS).
High Performance Computing is reaching the level of an ultimate tool empowering GSS to address extremely complex societal and scientific problems. By the nature of the problems addressed in typical GSS applications, the relevant datasets are mostly very big, and are expected to grow up tremendously as well as to include highly heterogeneous data sources.

High Performance Data Analysis (HPDA) is thus the key to the success of GSS in the next decade!

A key contribution of the Centre of Excellence for Global Systems Science will be the development of an HPC-based framework to generate customized synthetic populations for GSS applications. By enriching GSS applications to be fully supported by state-of-the-art HPC technologies, we will be able to provide decision-makers and civil society with detailed analyses, including real-time assessments, of global risks and opportunities.

CoeGSS will work with an integrative toolbox for global systems analysis. The integration will be centred on recent methodological advances in the construction and use of synthetic populations. A synthetic population provides a model of a given population, typically of humans, but if the need arises also of plants, animals, cars, buildings and more. The synthetic population is based on individuals that are different from the actual ones, but in such a way that the population as a whole matches the empirical one in the distribution of attributes and relations that matter for the problem at hand. CoeGSS will provide generators for such populations at a global, but also at smaller scales. They will include maps, datasets for empirical populations, algorithms for their dynamics, tools for statistical analysis and visualization instruments.

CoeGSS will use a portfolio of methods to take advantage of high-performance computing and big data. Its key strength is the fact that it can implement different methods with an explicit theoretical background, namely the theory of global systems. This approach is formulated on the basis of algorithmic game theory and a state-of-the-art understanding of socio-cultural evolution. To ensure that computer-based methods don’t run with the actual problems to be solved, CoeGSS will embed their use in stakeholder dialogues that provide an on-going feedback from practitioners.

CoeGSS carries out three pilot studies to apply these methods to selected global challenges:
the diffusion of health-relevant social habits, the possibility of green growth, and the dynamics of global urbanisation.