The Policy Compass approach, developed by Dr. Sotiris Koussouris, proposes a transparent and evidence-based framework for analyzing and evaluating government policies using open data, prosperity indicators, and argumentation technology. It aims to improve stakeholder engagement—such as citizens and policymakers—by facilitating the construction of metrics and models that visualize governmental impacts. By leveraging social media and deliberation platforms, the approach seeks to enhance the accountability and objectivity of public policy assessments.

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