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eGovernance Research Grand Challenges

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eGovernance Research Grand Challenges

  1. 1. A Roadmap for Research in Electronic Governance: <br />The Grand Challenges ahead<br />YannisCharalabidis<br />Assistant Professor, University of the Aegean<br />Manager, Greek Interoperability Centre<br />
  2. 2. Your keynote speaker<br />Software engineer, National Technical University of Athens<br />PhD in complex information systems, NTUA<br />7 years a researcher in RTD projects for businesses and governments<br />7 years in the software industry (Greece, Netherlands, Germany Poland). Managing director of Baan-Singular ERP company <br />Already 4 years in Uni Aegean, teaching and researching on eGovernance (another 3 “remaining”)<br />The next 7 years ?<br />My aim for the day: to give you food for thought. <br />Hold on …<br />
  3. 3. The problem: policy-making and governance in a complex world<br />Rising number of tipping points, unpredictable “black swan” events: (financial and economic crisis; terrorist attacks, climate change)<br />Can’t be adequately addressed by traditional econometric models<br />Politicians are not used to evidence-based decisions<br />Explosion in authorship, co-creation and collaboration<br />Mass collaboration and participation<br />Open data, open innovation models<br />Government 2.0<br />More intelligence and more stupidity, more signal and more noise<br />
  4. 4. Governance: often silos-based, linear, obscure, hierarchical, over-simplified<br />Policies, Disciplines and Actors are isolated<br />Society: increasingly interconnected, flexible, fast-evolving, unpredictable<br />The Problem: Gap between Society and Governance<br />
  5. 5. The problem: We need a mix of ICT with Social Sciences<br />Web Technologies<br />Systems & Services Technologies<br />“Hard”<br />Public Sector Service Systems <br />Workflow Systems<br />Enterprise Resource Management<br />Cloud computing<br />Web 2.0<br />Argument Visualization<br />Mixed Reality <br />Pattern Recognition<br />Serious Games<br />Electronic Participation<br />Translation Systems<br />Social Networks<br />PS Knowledge Management<br />Legal Structures Management<br />Business Intelligence<br />Data & Opinion Mining<br />Simulation<br />Forecasting - Backcasting<br />Optimization<br />Systems Dynamics<br />Adaptive Models<br />Behavioral Modelling<br />Societal Modelling<br />Social Simulation<br />Social Informatics<br />Management Tools<br />“Soft”<br />Society<br />Administration<br />
  6. 6. "The problems that we have created cannot be solved at the level of thinking that created them" Albert EinsteinSo ?<br />
  7. 7. A roadmap for ICT-enabled governance research, beyond 2010, to address global challenges: <br /><ul><li>What are the new needed research directions ?
  8. 8. How should we team-up among governments, industry and citizens ?
  9. 9. When should we expect results ?</li></ul><br />
  10. 10. 2020: A Paradigm Shift in Policy-making, using three "powers"<br />More people involved (collaborative governance)<br />2020<br />2010<br />More accurate and analytical, modeling and simulation tools <br />More data available (the data deluge)<br />
  11. 11. The Method<br />Future scenarios: demand pull<br />State of the art: research push<br />Gaps<br />Research roadmap (final)<br />Grandchallenges (draft)<br />Research challenges<br />Research challenges<br />
  12. 12. The eGovernance State of the Art in 2010<br />
  13. 13. High Openness & Transparency: extreme 1 <br />Self-Service <br />Governance<br />Open <br />Governance<br />Low Integration of Policy Intelligence<br />High Integration of Policy Intelligence<br />extreme 1<br />extreme 0<br />Leviathan <br />Governance<br />Privatised <br />Governance<br />Low Openness & Transparency: extreme 0<br />Four Scenarios for our Society<br />
  14. 14. WHAT – the Grand Challenges<br />
  15. 15. GC1: Model-based collaborative governance<br />Today’s policy modeling:<br />Human effort based<br />Using mainly econometric models and overlooking human behaviour<br />Social simulation and agent-based models are marginal, black-box, fragmented and single-purpose<br />Progress in modeling software has not matched advances in computing power.<br />Designing, reviewing and updating formal models from qualitative and quantitative data is costly.<br />
  16. 16. Research challenges<br />Integrated, composable and reusable models<br />models composability and interoperability (between software and modelling methods) to build on existing models<br />Short term research: definition of procedures for model composition and repositories <br />Long term research: model interoperability and SOA / GRID<br />Collaborative modelling<br />Intuitive model building and simulation tools to allow all stakeholders to take part in transparent formal modelling at large scale<br />Short term: transparent and intuitive modelling interfaces<br />Long-term: mass-collaboration modelling framework<br />Easy access to information and knowledge creation <br />methods of information elicitation that, during the overall model building and use processes, will help decision makers to learn how a certain system works and ultimately gain insights (knowledge) and understanding (apply the extracted knowledge from those processes) in order to successfully implement a desired policy.<br />Short-term: interoperability of data sources, information elicitation<br />Long-term: user-behavior information generation; mass-interactive learning environments<br />
  17. 17. Research challenges/2<br />Model validation<br />Reliability of models plays a crucial role in policy modeling and simulation. A policy model should be developed for a specific purpose (or context) and its validity is to be determined with respect to that purpose (or context). Therefore, specific and integrated techniques and ICT tools are required to be developed for policy modeling, (conceptual and software validation )<br />Short-term: Consolidation of validation techniques<br />Long-term: complex and large scale model validation; artificial intelligence incorporated in validation systems<br />Interactive simulation <br />It allows a researcher to interactively control simulations and perform data analysis while avoiding many of the pitfalls associated with the traditional batch/post processing cycle. <br />Short-term: Usability<br />Long-term: Input/output system integration, Computational steering<br />Output analysis and knowledge synthesis<br />the analysis and integration of feedbacks in modelling and simulation process<br />Short-term: Policy model simulation, ranking techniques<br />Long-term: sophisticated variance estimators, automated output analysis<br />
  18. 18. GC2: Data-powered collective intelligence and action<br />
  19. 19. Research challenges<br />Privacy-compliant participatory sensing for real-time policy-making<br />Dramatically increasing the data availability for policy evaluation while maintaining privacy and ensuring policy inference<br />Short term: combination of sensing with social network analysis, data quality verification, context verification; <br />Long term: privacy by design; enhanced analytical techniques to respond to subtle events; data collaboration protocols<br />Real-time, high-quality, reusable open government data <br />Simplifying and lowering costs of real-time open data publication, ensuring data quality and advanced privacy monitoring<br />Short-term: data vocabularies; data curating tools; easy linked data publication<br />Long-term: on the fly data quality agreements, web of data, real-time validation and publication<br />
  20. 20. Research challenges/2<br />Federated dynamic identity management and privacy control<br />Necessary to ensure trustful collaboration, federated across country, with multiple levels of security for different services, relying on authentic sources, usable in private sector context. <br />Short-term: Dynamic user-controlled data disclosure; culturally-dependent identity systems; trust negotiation<br />Long-term: context dependent identity management<br />Peer-to-peer public opinion mining<br />The limits of human attention, combined to the existing simple interfaces available for browsing discussion and comments, often leads to low levels of engagement and flaming wars, driving to polarisation of arguments and enhanced risks of conflicts.<br />Short-term research: computer-generated cross-language policy corpora; algorithms for policy statistical analysis; comment recommendation algorithms<br />Long-term research: integration with social network analysis; audiovisual mining; peer-to-peer usable opinion mining tools; <br />
  21. 21. Research challenges/3 <br />Intuitive, collaborative visual analytics of data for policy-making<br />Visual analytics is particularly effective when dealing with complex and non-predictable patterns, such as those related to assessing and anticipating public policy impact, but is not formalised in the policy context<br />Short-term research: Collaborative platform display; Interaction between visualization and models; Visualization infrastructures for policy modelling issues<br />Long-term research: Bias identification; learning adaptive algorithm for users’ intent; intuitive affordable interfaces for citizens<br />User-generated simulation and gaming tools for public action<br />Simulation and serious gaming impact on personal incentives to action and showing long-term and systemic effects of individual choices, but lack open scenarios based on personal and policy decision as well as usability<br />Short-term: kit-based citizens-controlled simulation and gaming; integration with policy models<br />Long-term: augmented reality in policy gaming and simulation<br />New institutional design of collaborative governance<br />
  22. 22. GC3 – Government Service UtilityRationale<br />Present:<br />Traditional public services have not delivered on their promise for time, quality, cost, or overall return on investment<br />Citizens rarely have access to personalised services in the way they want<br /> Service design cannot tap into citizen or SME’s productivity. Services practically remain the same as new service creation is hindered <br />Future:<br />Services are converging and moving from thephysical into the digital world, universally accessible on any device from all social groups<br />Government clouds are overcoming interoperability, privacy and security challenges and provide the base for high automation in public sectors<br />Future Internet appears as a key enabler for new public service systems, drastically altering productivity, speed, cost and overall quality<br />The 1-1-1 Concept:<br />every service can be provided in one stop, one second, with one euro cost<br />
  23. 23. Why a Service Utility ? <br /> Electricity Provision Service Provision<br />Ubiquitous nature: electricity is available everywhere, if you have a proper line and device to connect<br />Usability: it is simple to connect to electricity network, provided you have an electric device with a standard plug (different from country to country, sometimes)<br />Federation: you don’t really know where / how energy is created within a complex network that cross borders, sectors<br />Co-generation: you can be a customer and a provider, at the same time<br />De-regulation: although Governments set the regulations and may own some utilities, the market is competitive<br />Multi-channel service provision<br />Simplicity, interoperability, inclusion<br />Public Clouds <br />Service co-creation<br />Service supply deregulation<br /> See also “6 common characteristics of service utilities (Rappa, 2004)”: Necessity, Reliability, Usability, Utilisation, Scalability and Exclusivity.<br />
  24. 24. The GSU Model <br />Enterprises, SME’s, VSE’s<br /><ul><li> Finance
  25. 25. Growth
  26. 26. Work and Social Security
  27. 27. Representation
  28. 28. Information </li></ul>Administrations<br /><ul><li> CoreServices
  29. 29. Registry Services
  30. 30. Public Sector (web) Services
  31. 31. Planning
  32. 32. Monitoring
  33. 33. Open Data</li></ul>Citizens<br /><ul><li> Citizenship
  34. 34. Health
  35. 35. Education
  36. 36. Work and Social Security
  37. 37. Representation / Participation
  38. 38. Finance
  39. 39. Information</li></ul>Other / Cross Country GSU’s<br /><ul><li> PanEuropean Core Services
  40. 40. PanEuropean Registry Services
  41. 41. Cross-country services
  42. 42. Highly automated </li></ul> cross-GSU Services <br /><ul><li> Private Service Utilities </li></ul>Service<br />Provision<br />GSU<br />Service Consumption<br />Service Creation<br />Service<br />Aggregation<br />Information Services<br /><ul><li> Open data
  43. 43. Semantic services
  44. 44. Knowledge management</li></ul>Core Services<br /><ul><li> Identification
  45. 45. Security
  46. 46. Communication
  47. 47. Storage
  48. 48. Execution
  49. 49. Open Data</li></ul>Registry Services<br /><ul><li> Citizen Registry
  50. 50. Health Registry
  51. 51. Financial Registry
  52. 52. Cadastre
  53. 53. Social Security
  54. 54. Education
  55. 55. Professional Chamber</li></ul>Complex Services<br /><ul><li> Taxation
  56. 56. Health
  57. 57. Education
  58. 58. Social Security
  59. 59. Benefits / subsidies
  60. 60. Representation / Participation</li></li></ul><li>GC3 Research challenges<br />User-driven innovation shaping Public Services<br />Service co-design, co-generation, mashing and deployment<br />Citizen generated ideas for new services <br />Change the “DNA” of Public Services<br />Cloud – based service provision, high automation, interoperability <br />Multichannel provision, internet of things<br />Services in one second, one stop, at one euro cost<br />Digital public services value proposition for all<br />Reshape digital public services objectives, scope and means <br />Create a value proposition model for all stakeholders <br />Massive Public Information as a Service<br />Utilisation of public information and knowledge<br />
  61. 61. The Governance Cycle and the Management Cycle<br />Citizens<br />GC 1<br />GC 2<br />State<br />GC 3<br />Citizens<br />
  62. 62. GC4 – Science Base for ICT-enabled GovernanceRationale<br />Present:<br /> Although a lot of solutions are being developed and applied, there is a lack of systematisation of the domain, hindering re-use of practices, gradual refinement and evolution<br /> Relations with neighboring domains are not explored, resulting in unnecessary duplications or lack of cooperation<br />Future:<br /> ICT-enabled governance is maturing into a well-established discipline, integrating social sciences, management, operational research and ICT<br /> Classification of research approaches, applications, problems and solution paths supports gradual evolution<br /> The research community is constantly updating the objectives and challenges of the domain, utilising new ICT developments for the good of the society<br />
  63. 63. Multi-disciplinary issues and relations with neighbouring domains<br />Metrics and assessment models, Decision Support, Modelling & Simulation Tools (supporting problem-solution relation, utilising BPM/BPR tools, vertical approaches)<br />Formal methods and tools for categorising and analysing the concepts, the problems and solution paths in ICT-enabled governance<br />GC4: Research Challenges<br />
  64. 64. A collaborative journey…<br />3 large experts’ workshops: <br />Samos restricted workshop in July 2010 (over 100 participants)<br />Roadmap Validation workshop in conjunction with the IFIP EGOV Conference 2010, on August 30th, 2010 (over 50 participants) <br />Networking Session (Large Expert Workshop) in conjunction with the ICT 2010 Conference in Brussels on September 27th, 2010 (over 100 participants)<br />Online deliberation at (over 500 votes)<br />Validation by the Experts Scientific Committee of the full draft of the initial roadmap<br />Ongoing discussion on LinkedIn group<br />Average distribution: 30% industry, 10% public administration, 60% researchers<br />
  65. 65.
  66. 66. My eGovernance Research Hype Curve<br />Visibility<br />Service Co-creation<br />Visual Analytics<br />Gov Cloud (SaaS)<br />Linked Data<br />Open data <br />Model-Based Decision Making<br />Opinion Mining<br />Social Media in Policy Making<br />Service Delivery Platforms<br />Organisational Interoperability<br />Legal Informatics<br />Gov Cloud (IaaS)<br />eParticipation<br />Argument Visualisation<br />Gov Cloud (PaaS)<br />eVoting<br />Societal Simulation<br />Instant, proactive Service Delivery for all<br />Semantic Interoperability<br />Mobile Government<br />Web Services<br />Science Base<br />for ICT-enabled Governance<br />Federated eID<br />Technical Interoperability<br /> ICT-enabled historiography<br />Inflated Expectations<br />Disillusionment<br />Productivity<br />Time<br />
  67. 67. Back to reality: Our current projects on ICT-enabled Governance<br />PADGETS: Policy Making through Social Media Interoperability<br />ENGAGE: Open, Linked Governmental Data for scientists and citizens<br />NOMAD: Non-moderated opinion mining (the opinion web) – starting October 2011<br />CROSSOVER: A global think-tank on ICT-enabled Governance– starting October 2011<br />
  68. 68. As a conclusion<br />We need a totally different set of tools for evidence-based decision making by governments<br />Societal Simulation, Data and Opinion Mining, Service Co-creation will be the next “big things” for governments that wish to make a difference<br />We need to go beyond pure ICT approaches and embark in a multi-disciplinary journey. That’s why we need a science base for ICT-enabled Governance<br />But most importantly …<br />
  69. 69. eGovernance Research is about our children’s future:<br />It is not enough to “do things right” … <br />we should “do the right things”<br />Stay tuned at:<br /><br />@yannisc<br /> <br />

Editor's Notes

  • Power law distribution, Tipping points, Cascade effectsLiquid modernity, Flat world, Chaos theoryPermanent instability and critical state
  • Present:collaborative policy making requires in-depth understanding and attention, and involves only a self-selected micro-elites of participants with total separation from non-participants and risks of group thinking. When large-scale participation occurs, input is often of low value or confrontational and data processing is mostly human, at high cost. Costs of engagement and analysis remain high, and online-discussion too separated from mainstream prioritieseven in cases where online collaboration happens, little real-world action derives. Even when ICT provides sufficient evidence, this does not translate into concrete action by government and citizens, because of confirmation bias, risk aversion, lack of attention, lack of incentives – as in the case of climate change.