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

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

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 Foraging Policy Design Impact Analysis

Tobias Ruppert

Policy Modeling Process – Impact Analysis

 Use the extracted information for the design of policies  Analyze available data with visual analytics techniques, e.g.

 Demographical information  Financial information  Geographical information  …

 Take into account public

• pinions

 Opinion Mining  Sentiment Analysis  Argument Extraction  …

 Enable non-expert users to get access to this information  Evaluate the impact of designed policy

Ex ante – e.g., with simulation methods Ex post – e.g., via changing opinions, statistical analysis of actual impacts Information Foraging Policy Design Impact Analysis

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

 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

Visual Support for Policy Modeling

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

• f complex global decision making.

 Use Case: Development of a sustainable regional energy plan

Tobias Ruppert

ePolicy – Engineering the policy making life-cycle

Tobias Ruppert

 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

• pinions and wishes

 Game theory

 for regulating their interaction

 Opinion Mining

 for extracting social attitudes

ePolicy – Engineering the policy making life-cycle

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

• ptimal 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

• pinions and arguments

Tobias Ruppert

Examples: Visualization for Opinion Mining

• D. Oelke et al (2009)

Tobias Ruppert

Generalization of Visualization Concepts

Input Parameters

• f Agents

Constraints and Target Fuction

• f Optimization

Problem

Model Agent-based Simulation Optimization Solver Output Simulation Result Optimal Solution Simulation Opinion Mining Metadata Opinions, Arguments Optimization Opinion Mining Visual Analysis of Dependencies between Input and Output of Models

Tobias Ruppert

 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

Conclusion

Thank you! Any questions?

Tobias Ruppert

• Dept. Information Visualization and Visual Analytics

Fraunhofer Institute for Computer Graphics Research Darmstadt tobias.ruppert@igd.fraunhofer.de