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Visions in Global Systems Science: Models and Data

Public policy making, when addressing challenges such as climate change, financial crises, or containment of pandemics, suffers from an intrinsic difficulty: these global challenges generate strong interdependencies between different social, technological, and natural systems. In dealing with them, societies tend to address individual systems, rather than multiple interrelated systems, and thereby fail to achieve systemic change.

The vision is to integrate scientific evidence into the social processes leading to policy decisions addressing global challenges. The ICT engines driving GSS are large-scale computing platforms to simulate highly interconnected systems to make full use of the abundance of data on social, economic, technological and ecological systems available today. The unprecedented in scale and scope of these data represents a step change in how science is able to address societal questions. Equally important are online social media and collaborative ICT platforms that support active participation of all stakeholders in the process of gathering and analysing (scientific) evidence and thereby in the policy process.

Research Objectives as Two Complementary Strands:

  • Policy informatics – scientific evidence-base for policy: ICT tools to provide models and data highly integrated across different policy sectors;
  • Societal informatics – a society-centered science: ICT tools - presenting model results via games or visualising data- integrate the scientific evidence-base in the policy processes. Social media and participatory ICT platforms to link better stakeholders in the scientific and policy process.

The Visions in Global Systems Science: Models and Data workshop mainly addressed 'policy informatics' aspects of GSS, that is the role of data and models.

Decision makers facing global challenges increasingly use computer models, simulation as well as large scale heterogeneous data and try to integrate and make sense of information in order to turn it into knowledge available for a future course of action. There is mounting concern that even with the use of such simulations and models we do not know enough to make effective decisions in response to global challenges. What is more, we also don’t know enough about our methods of modeling complex systems of this size by computer simulation to be able to effectively operate. A quite more rigorous foundation is necessary to comprehend the deep interplay of systems simulations, data from various sources and the actual problems we are facing as a society.

Scope of the workshop will be exploring role and interest of various computer science and mathematical approaches pertinent in this context: from interaction based computing to data topology and modeling languages, from high performance computation to novel data mining methodologies. In particular, the most efficient methods for specification and analysis of dynamics of highly interconnected systems, specification, verification and validation of the computational dynamics simulations; formal approach to the analysis of dynamical network abstractions for complex system representation. Explicit applications to different contexts will be discussed. The aim is to propose new viable ways to validate, verify and specify computer-based simulation of highly interconnected systems which might help decision makers in a truly interconnected, socio-technical, data-driven global society.

Questions

  • 1. ICT tools and research challenges in GSS: What are the research challenges and obstacles that need to be addressed in the two research strands of policy and societal informatics?
  • 2. What are the challenges for research in ICT (and beyond) resulting from the GSS vision? What are GSS specific challenges and what are challenges shared with other modelling and data research activities?
  • 3. How can IT infrastructures (HPC, e-infrastructures and cloud, Big Data, and social media) be put to use in GSS? What are the fundamental challenges that GSS poses to ICT research?
  • 4. What is prediction in this context (given that data and models are presumed to have inherent knowledge to be extracted)? Which connections or interfaces with other fields of science do we need to translate ICT hard data into soft information for society and politics?

Themes

  • 1. Computer Science for interacting Informational, Technological and Social Networks
  • 2. The Mathematics and Computer Science of very large systems: not only high performance computing, but data-driven science as well
  • 3. Advanced computing for Network Science Network Science as an integrating framework for real world complexity
  • 4. Network approach for governance and policy tools for societal action in response to global challenges.
Date & Time: 
Thursday, 7 February, 2013 - 10:00 to Friday, 8 February, 2013 - 15:30
Venue: 
European Commission
Event Type: 
workshop
Hosts: 
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