Regular Article

The European Physical Journal Special Topics

, Volume 214, Issue 1, pp 109-152

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Towards a global participatory platform

Democratising open data, complexity science and collective intelligence
  • S. Buckingham ShumAffiliated withKnowledge Media Institute, The Open University
  • , K. AbererAffiliated withDistributed Information Systems Laboratory, École Polytechnique Fédérale de Lausanne, EPFL-IC-IIF-LSIR, Bâtiment BC
  • , A. SchmidtAffiliated withInstitut für Visualisierung und Interaktive Systeme, Universität Stuttgart, Universitätstraße 38
  • , S. BishopAffiliated withDept. Mathematics, University College London
  • , P. LukowiczAffiliated withEmbedded Systems Lab, University of Passau, IT-Zentrum/International House
  • , S. AndersonAffiliated withSchool of Informatics, University of Edinburgh
  • , Y. CharalabidisAffiliated withInformation Systems Laboratory, University of the Aegean
  • , J. DomingueAffiliated withKnowledge Media Institute, The Open University
  • , S. de FreitasAffiliated withSerious Games Institute, Coventry Innovation Village, Coventry University Technology Park
    • , I. DunwellAffiliated withSerious Games Institute, Coventry Innovation Village, Coventry University Technology Park
    • , B. EdmondsAffiliated withCentre for Policy Modelling, Manchester Metropolitan University
    • , F. GreyAffiliated withCitizen Cyberscience Centre, CERN, UNOSAT
    • , M. HaklayAffiliated withDept. Civil, Environmental and Geomatic Engineering, University College London
    • , M. JelasityAffiliated withResearch Group on Artificial Intelligence, Hungarian Academy of Science and University of Szeged
    • , A. KarpištšenkoAffiliated withSkype Labs, Skype
    • , J. KohlhammerAffiliated withFraunhofer-Institut für Graphische Datenverarbeitung IGD
    • , J. LewisAffiliated withDept. Anthropology, University College London
    • , J. PittAffiliated withDept. Electrical & Electronic Engineering, Imperial College London
    • , R. SumnerAffiliated withDisney Research Zurich
    • , D. HelbingAffiliated with


The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.

Graphical abstract