The Visual Policy Making Life-Cycle: Supporting Policy Makers with - PowerPoint PPT Presentation

The Visual Policy Making Life-Cycle: Supporting Policy Makers with Visual-Interactive ICT Tools for Sustainable Policy Making Tobias Ruppert Dept. Information Visualization and Visual Analytics Fraunhofer Institute for Computer Graphics Research Darmstadt tobias.ruppert@igd.fraunhofer.de

Overview  Motivation  Policy modeling process  Visual support for policy modeling  An example: ePolicy – a short project introduction  Visualization concepts  Conclusion and discussion Tobias Ruppert

Motivation – Sustainable Policy Making  Goal: Sustainable political decisions taking into acocount  Environmental  Economical and  Social aspects  Challenge: Support politicians in agenda setting with ICT tools  Problem: Politicians are mostly no IT-experts  Goal: Support decision makers with different levels of expertise with visualization tools for applying complex ICT tools during policy modeling process Tobias Ruppert

Overview  Motivation  Policy Modeling Process  Visual support for policy modeling  An example: ePolicy – a short project introduction  Visualization concepts  Conclusion and Discussion Tobias Ruppert

Policy Modeling Process Information Policy Impact Foraging Design Analysis Tobias Ruppert

Policy Modeling Process – Impact Analysis  Analyze available data with  Use the extracted information for the visual analytics techniques, e.g. design of policies  Demographical information  Financial information  Geographical information Information Policy Impact  … Foraging Design Analysis  Take into account public opinions  Opinion Mining  Sentiment Analysis  Evaluate the impact of designed policy  Argument Extraction  Ex ante – e.g., with simulation methods  …  Ex post – e.g., via changing opinions,  Enable non-expert users to get statistical analysis of actual impacts access to this information Tobias Ruppert

Overview  Motivation  Policy Modeling Process  Visual support for policy modeling  An example: ePolicy – a short project introduction  Visualization concepts  Conclusion and Discussion Tobias Ruppert

Visual Support for Policy Modeling Tobias Ruppert

Visual Support for Policy Modeling  Understanding policy modeling on different levels of expertise  From information design for non-IT-experts  No analysis, no interaction  just visual representation of analysis results  To visual analytics for policy analysts with It-expertise  visual-interactive analysis of large datasets  visual control of complex analysis algorithms Tobias Ruppert

Overview  Motivation  Policy Modeling Process  Visual support for policy modeling  An example: ePolicy – a short project introduction  Visualization concepts  Conclusion and Discussion Tobias Ruppert

ePolicy – Engineering the policy making life-cycle  Research project funded by the European Commission  Scope: eGovernment and policy modeling  Goal: Provide policy makers with integrated models, visualization, simulation and opinion mining techniques that improve the oucomes of complex global decision making.  Use Case: Development of a sustainable regional energy plan Tobias Ruppert

ePolicy – Engineering the policy making life-cycle Tobias Ruppert

ePolicy – Engineering the policy making life-cycle  Global level optimization  global objectives, financial aspects, impact assessment on economy, society and environment on large scale  Individual level agent-based simulation  simulating social behaviour regarding new policies taking into account individual opinions and wishes  Game theory  for regulating their interaction  Opinion Mining  for extracting social attitudes Tobias Ruppert

Visualization Concepts  Visualization support for individual technologies  Optimization  Agent-based simulation  Opinion Mining  Visualization support for the integrated pipeline Tobias Ruppert

Visualization Concepts for Optimization  Input Parameters  Target function  Constraints  Output Data  optimal solution  Task: Visually explore dependencies between parameters and optimal solution Tobias Ruppert

Examples: Visualization for Optimization Y.-H. Chan et al (2010) Tobias Ruppert

Visualization Concepts for Simulation  Input Parameters  Agent parameters  Environment parameters  Output Data  Simulation outcome  Task: Visually explore dependencies between input parameters and simulation outcome Tobias Ruppert

Examples: Visualization for Simulation R.J. Crouser et al (2012) Tobias Ruppert

Visualization Concepts for Opinion Mining  „Input Parameters  meta information about statement holder  Output Data  opinions  arguments  Task: Visually explore dependencies between meta information and opinions and arguments Tobias Ruppert

Examples: Visualization for Opinion Mining D. Oelke et al (2009) Tobias Ruppert

Generalization of Visualization Concepts Input Model Output Parameters Agent-based Simulation Simulation of Agents Simulation Result Constraints and Optimization Optimal Target Fuction Optimization of Optimization Solver Solution Problem Opinion Opinions, Metadata Opinion Mining Mining Arguments Visual Analysis of Dependencies between Input and Output of Models Tobias Ruppert

Conclusion  The Policy Modeling Process  Visual Support for Policy Modeling  ePolicy life-cycle  Visualization Examples  Generalization of Visualization Concepts  Final Statement: Use visualization to  provide non-experts with complex analysis tools  explore the problem space and detect interdependencies between input and output data Tobias Ruppert

Thank you! Any questions? Tobias Ruppert Dept. Information Visualization and Visual Analytics Fraunhofer Institute for Computer Graphics Research Darmstadt tobias.ruppert@igd.fraunhofer.de