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Towards more factual, evidence-based, transparent and 
accountable policy evaluation and analysis: 
The Policy Compass approach 
Dr. Sotiris Koussouris 
DSSlab – NTUA 
Greece 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Problem, Motivation and Approach 
The Problems 
1. Internet has evolved into a rich 
source for information but also to 
an instrument of spreading 
misinformation and propaganda 
2. Lack of consensus about a 
suitable metric for measuring 
progress 
3. Difficulty of objectively assessing 
the impacts of government policies 
The Proposed Approach 
I. Open Public Data 
II. Prosperity Indicators 
III. Fuzzy Cognitive Maps 
IV. Argumentation Technology 
V. Deliberation Platforms and 
Social Media 
Improve the quality and 
transparency of the policy 
analysis and evaluation phases 
of the policy cycle for a variety 
of stakeholders, ranging from 
citizens to policy makers 
Analysis 
Policy 
cycle 
Implementation 
/Monitoring 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
The Policy Compass Approach 
• A research prototype of an easy-to-use, highly visual and intuitive tool for: 
– Constructing prosperity and other policy metrics with an easy-to-use 
visual language for defining variables and functions over open data sources. 
– Constructing graphs and charts visualizing metrics for selected 
geographical regions and time periods. 
– Annotating graphs and charts with political or policy events. 
– Building causal models with an easy-to-use visual tool for Fuzzy Cognitive 
Maps (FCM). 
– Sharing and debating prosperity graphs and FCM across popular social 
media platforms. 
– Summarizing and visualizing the debates in argument maps and 
conducting structured surveys about policy issues 
– Aggregating opinions on policy issues, to formulate a common position in a 
party or interest group. 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Pillar I: Prosperity Indexes 
• Prosperity metrics capture the level of welfare and quality of life in a 
given region or society. 
• Prosperity is a vague and subjective concept with essential 
psychological, social and economic aspects. 
• There is no consensus about how to objectively measure prosperity 
• Indicators of economic growth: 
– Gross Domestic Product (GDP) 
– Genuine Progress Index (GPI) 
– Index of Sustainable Economic Welfare (ISEW) 
– GINI Index 
• Alternatives: 
– Human Development Index (HDI) 
– Legatum Prosperity Index 
– “Healthy life years statistics” by Eurostat 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Pillar II: Open Public Data 
• Open and unrestricted access to large scale data sets is essential for 
political engagement and scientific research 
• Available large scale data sets have nowadays their own self-contained 
existence rules. 
• Micro-data can be used to construct new indicators of multifaceted 
nature. 
• Sources of micro-data: 
– Eurobarometer surveys 
– European Union Statistics on Income and Living Conditions (EU-SILC) by 
Eurostat 
– Urban Audit (the European cities Eurostat) 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Pillar III: Fuzzy Cognitive Maps 
• A well-founded, general-purpose and intuitive method for modelling and 
simulating relationships between variables. 
• Introduced by B. Kosko (1986) as a fuzzified version of Cognitive Maps, 
originally introduced by political scientist R. Axelrod (1976). 
• A fuzzy directed graph of nodes and edges, where nodes represent fuzzy 
concepts, describing behavioral characteristics of a system that occur to some 
degree, and directed edges represent the causal relationships among these 
concepts. 
• The graph edges are weighted by a real 
value from the interval [-1, 1], which 
expresses the strength of the relation 
between two concepts. 
• FCMs have been widely used to model 
and simulate policies and their effects. 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Pillar IV: Argumentation Technology 
• Argumentation support systems are computer software for helping people 
participate in various kinds of goal-directed dialogues in which arguments are 
exchanged. 
• The idea of using argumentation support systems for eParticipation can be 
traced back at least to Horst Rittel’s pioneering work in the early 1970s who 
used visual maps of arguments, to help people collaborate and find solutions to 
what he called “wicked problems”. 
• “Wicked problems” have no algorithmic, scientific or objectively optimal 
solutions for a variety of reasons, including the lack of consensus among 
stakeholders about utilities and values. 
• Typically, eParticipation projects make use of generic groupware systems (e.g. 
discussion fora, online surveys, etc.) not providing though specific technical 
support for argumentation. 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Pillar V: Deliberation Platforms and Social 
Media 
• Deliberation platforms incarnate the efforts taken by government 
agencies, to increase citizens’ engagement in their decision and policy 
making processes. 
• The first wave of deliberation platforms has witnessed extensive 
information on government activities, decisions, plans and policies, the 
proliferation of e-voting and e-consultation spaces, along with various 
types of e-fora. 
• Still, the first generation of deliberation platforms did not meet the 
original expectations. 
• The advent of Web 2.0 tools has created a more vivid environment and 
the popularity of the social media has set a new battlefield for the 
concept of e-Participation. 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Policy Compass Pillars’ Relations 
Pillar I: 
Prosperity 
Indexes 
Pillar II: Open 
Public Data 
Pillar III: Fuzzy 
Cognitive Maps 
Pillar IV: 
Argumentation 
Pillar V: 
Deliberation 
Platforms & 
Social Media 
Pillar I: 
Prosperity 
Indexes 
Pillar II: Open 
Public Data 
Pillar III: Fuzzy 
Cognitive Maps 
Pillar IV: 
Argumentation 
Pillar V: 
Deliberation 
Platforms & 
Social Media 
Define higher 
level metrics 
from lower level 
Define higher 
level metrics 
from lower level 
ones 
ones 
Construct 
metrics by 
operationalizing 
open data 
sources 
Use historical 
events to 
annotate metric 
visualizations 
Access open data 
Access open data 
sources, 
sources, 
Publish data sets 
& their metadata 
Publish data sets 
& their metadata 
Develop ideas on 
the correlations 
among policies and 
prosperity 
fluctuations 
Simulate causal 
policy models 
based on open 
data sets 
Debate on 
prosperity 
metrics 
Reuse 
argumentation 
outcomes as 
structured open 
data 
Share own 
developed 
prosperity 
metrics 
Predict the 
evolution of 
prosperity 
indicators by 
applying causal 
policy models 
Use historical 
data to validate 
causal policy 
models 
Weigh prosperity 
aspects 
according to the 
opinions 
expressed 
Use open public 
data to bolster 
one’s opinion 
Develop and 
apply own causal 
policy models 
Develop and 
apply own causal 
policy models 
Define the 
strength of 
correlations 
according to the 
opinions 
expressed 
Debate on 
causal models 
underlying 
policies 
Summarize and 
visualize debates 
in argument 
Summarize and 
visualize debates 
in argument 
maps 
maps 
Share own 
developed causal 
policy models 
Poll public 
opinion on policy 
issues 
Define prosperity 
metrics 
collectively 
Define policy 
impact models 
collectively 
Aggregate poll 
outcomes to 
formulate a 
common position 
Ensure citizens’ 
Ensure citizens’ 
wide 
wide 
participation 
participation 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Use Case Walkthrough 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Discussion and Conclusions 
• A framework for empowering citizens and policy makers to better 
assess government policies. 
• Benefits of the approach: 
Decision makers: 
• Visualize the effects of their politics 
• Stimulate public debate 
• Communicate policy outcomes to 
citizens clearer 
• Build confidence in progress 
towards societal goals 
Citizens: 
• Engage in the development of 
prosperity indices 
• Monitor and critically discuss the 
quality of public policies 
• Learn about the multiple 
dimensions and social and 
economic consequences of policies 
• Improve the objectivity and 
evidential basis of their arguments 
• Assessment and validation in real case pilots (UK and Russia). 
• Are user-generated metrics trustworthy? 
• How is prosperity measured? 
• Can prosperity be measured in the same way for all? 
• …..? 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
Thank you 
Dr. Sotiris Koussouris 
skous@me.com 
DSSLab - NTUA 
Policy Compass received funding from the European Union’s Seventh Framework Programme for research, 
technological development and demonstration 
Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass

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Policy Compass at eChallenges 2014

  • 1. Towards more factual, evidence-based, transparent and accountable policy evaluation and analysis: The Policy Compass approach Dr. Sotiris Koussouris DSSlab – NTUA Greece Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 2. Problem, Motivation and Approach The Problems 1. Internet has evolved into a rich source for information but also to an instrument of spreading misinformation and propaganda 2. Lack of consensus about a suitable metric for measuring progress 3. Difficulty of objectively assessing the impacts of government policies The Proposed Approach I. Open Public Data II. Prosperity Indicators III. Fuzzy Cognitive Maps IV. Argumentation Technology V. Deliberation Platforms and Social Media Improve the quality and transparency of the policy analysis and evaluation phases of the policy cycle for a variety of stakeholders, ranging from citizens to policy makers Analysis Policy cycle Implementation /Monitoring Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 3. The Policy Compass Approach • A research prototype of an easy-to-use, highly visual and intuitive tool for: – Constructing prosperity and other policy metrics with an easy-to-use visual language for defining variables and functions over open data sources. – Constructing graphs and charts visualizing metrics for selected geographical regions and time periods. – Annotating graphs and charts with political or policy events. – Building causal models with an easy-to-use visual tool for Fuzzy Cognitive Maps (FCM). – Sharing and debating prosperity graphs and FCM across popular social media platforms. – Summarizing and visualizing the debates in argument maps and conducting structured surveys about policy issues – Aggregating opinions on policy issues, to formulate a common position in a party or interest group. Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 4. Pillar I: Prosperity Indexes • Prosperity metrics capture the level of welfare and quality of life in a given region or society. • Prosperity is a vague and subjective concept with essential psychological, social and economic aspects. • There is no consensus about how to objectively measure prosperity • Indicators of economic growth: – Gross Domestic Product (GDP) – Genuine Progress Index (GPI) – Index of Sustainable Economic Welfare (ISEW) – GINI Index • Alternatives: – Human Development Index (HDI) – Legatum Prosperity Index – “Healthy life years statistics” by Eurostat Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 5. Pillar II: Open Public Data • Open and unrestricted access to large scale data sets is essential for political engagement and scientific research • Available large scale data sets have nowadays their own self-contained existence rules. • Micro-data can be used to construct new indicators of multifaceted nature. • Sources of micro-data: – Eurobarometer surveys – European Union Statistics on Income and Living Conditions (EU-SILC) by Eurostat – Urban Audit (the European cities Eurostat) Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 6. Pillar III: Fuzzy Cognitive Maps • A well-founded, general-purpose and intuitive method for modelling and simulating relationships between variables. • Introduced by B. Kosko (1986) as a fuzzified version of Cognitive Maps, originally introduced by political scientist R. Axelrod (1976). • A fuzzy directed graph of nodes and edges, where nodes represent fuzzy concepts, describing behavioral characteristics of a system that occur to some degree, and directed edges represent the causal relationships among these concepts. • The graph edges are weighted by a real value from the interval [-1, 1], which expresses the strength of the relation between two concepts. • FCMs have been widely used to model and simulate policies and their effects. Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 7. Pillar IV: Argumentation Technology • Argumentation support systems are computer software for helping people participate in various kinds of goal-directed dialogues in which arguments are exchanged. • The idea of using argumentation support systems for eParticipation can be traced back at least to Horst Rittel’s pioneering work in the early 1970s who used visual maps of arguments, to help people collaborate and find solutions to what he called “wicked problems”. • “Wicked problems” have no algorithmic, scientific or objectively optimal solutions for a variety of reasons, including the lack of consensus among stakeholders about utilities and values. • Typically, eParticipation projects make use of generic groupware systems (e.g. discussion fora, online surveys, etc.) not providing though specific technical support for argumentation. Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 8. Pillar V: Deliberation Platforms and Social Media • Deliberation platforms incarnate the efforts taken by government agencies, to increase citizens’ engagement in their decision and policy making processes. • The first wave of deliberation platforms has witnessed extensive information on government activities, decisions, plans and policies, the proliferation of e-voting and e-consultation spaces, along with various types of e-fora. • Still, the first generation of deliberation platforms did not meet the original expectations. • The advent of Web 2.0 tools has created a more vivid environment and the popularity of the social media has set a new battlefield for the concept of e-Participation. Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 9. Policy Compass Pillars’ Relations Pillar I: Prosperity Indexes Pillar II: Open Public Data Pillar III: Fuzzy Cognitive Maps Pillar IV: Argumentation Pillar V: Deliberation Platforms & Social Media Pillar I: Prosperity Indexes Pillar II: Open Public Data Pillar III: Fuzzy Cognitive Maps Pillar IV: Argumentation Pillar V: Deliberation Platforms & Social Media Define higher level metrics from lower level Define higher level metrics from lower level ones ones Construct metrics by operationalizing open data sources Use historical events to annotate metric visualizations Access open data Access open data sources, sources, Publish data sets & their metadata Publish data sets & their metadata Develop ideas on the correlations among policies and prosperity fluctuations Simulate causal policy models based on open data sets Debate on prosperity metrics Reuse argumentation outcomes as structured open data Share own developed prosperity metrics Predict the evolution of prosperity indicators by applying causal policy models Use historical data to validate causal policy models Weigh prosperity aspects according to the opinions expressed Use open public data to bolster one’s opinion Develop and apply own causal policy models Develop and apply own causal policy models Define the strength of correlations according to the opinions expressed Debate on causal models underlying policies Summarize and visualize debates in argument Summarize and visualize debates in argument maps maps Share own developed causal policy models Poll public opinion on policy issues Define prosperity metrics collectively Define policy impact models collectively Aggregate poll outcomes to formulate a common position Ensure citizens’ Ensure citizens’ wide wide participation participation Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 10. Use Case Walkthrough Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 11. Discussion and Conclusions • A framework for empowering citizens and policy makers to better assess government policies. • Benefits of the approach: Decision makers: • Visualize the effects of their politics • Stimulate public debate • Communicate policy outcomes to citizens clearer • Build confidence in progress towards societal goals Citizens: • Engage in the development of prosperity indices • Monitor and critically discuss the quality of public policies • Learn about the multiple dimensions and social and economic consequences of policies • Improve the objectivity and evidential basis of their arguments • Assessment and validation in real case pilots (UK and Russia). • Are user-generated metrics trustworthy? • How is prosperity measured? • Can prosperity be measured in the same way for all? • …..? Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass
  • 12. Thank you Dr. Sotiris Koussouris skous@me.com DSSLab - NTUA Policy Compass received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass