BU3561 - Services and Information Management School of Business Trinity College Dublin Week 11, 23 March 2015 9-11 AM Tracey P. Lauriault Programmable City Project, NIRSA, Maynooth University

1. School of Business
Trinity College Dublin
Week 11, 23 March 2015
9-11 AM
Tracey P. Lauriault
Programmable City Project, NIRSA, Maynooth University
BU3561 - Services and Information Management
Evidence-Informed
Decision Making

2. Table of Contents
1. Introduction to the Programmable City Project
2. Urban indicators, city benchmarking and real-
time dashboards (Kitchin, Lauriault & McArdle 2015)
3. City Indicator & Benchmaking Systems
a) Federation of Canadian Municipalities (FCM) Quality of
Life Indicator System (QoLRS)& Municipal Data Collection
Tool (MDCT)
b) Dublin Dashboard
4. Open Data Indicators
a) Open Knowledge Foundation Index
b) G8 Open Data Charter

3. The Programmable City

4. The Programmable City
• A European Research Council (ERC: €2.3m) and
Science Foundation of Ireland (SFI: €200k) funded
• SH3: Environment and Society
• Team of 11 researchers
• 1 PI; 4 Pd Researchers; 5 PhD students
• Key themes: smart cities, software, ubiquitous
computing, locative media, big and open data
• Primary site: Dublin; Secondary site: Boston
• 5 years (started June 2013)

5. MIT Press 2011 Sage 2014
Aim of the ERC
project is to build
off and extend a
decade of work that
culminated in
Code/Space book
(MIT Press) with a set
of detailed empirical
studies
Aim

6. Objectives
How is the city translated into software and data?
How do software and data reshape the city?
Translation:
City into Code/Data
Transduction:
Code/Data Reshapes City
THE CITYSOFTWARE
Discourses, Practices, Knowledge, Models
Mediation, Augmentation, Facilitation, Regulation

7. Sub-Projects
Translation:
City into code & data
Transduction:
Code & data reshape city
Understanding the
city
(Knowledge)
How are digital data materially &
discursively supported & processed
about cities & their citizens?
(Tracey, PdR)
How does software drive public
policy development &
implementation?
(Bob /Aoife PhDs)
Managing
the city
(Governance)
How are discourses & practices of
city governance translated into code?
How is software used to regulate &
govern city life? (Jim, PhD)
Working
in the city
(Production)
How is the geography & political
economy of software production
organised? (Alan, PhD)
How does software alter the form
& nature of work? (Leighton, PdR)
Living
in the city
(Social Politics)
How is software discursively
produced & legitimated by vested
interests? (Darach, PhD)
How does software transform the
spatiality & spatial behaviour of
individuals? (Sung-Yueh, PdR)
Creating the
smart city
Dublin Dashboard (Gavin, PdR)

8. Urban indicators, city benchmarking &
real-time dashboards
(Kitchin, Lauriault & McArdle 2015)

9. 4 sections
1.Different types of indicators
2.Drivers & how employed
3.Critical appraisal
4.Acknowledge:
• Cities are more than disassembled facts
• Indicators, benchmarks & dashboards shape &
frame cities
• They are assemblages

10. Measuring
• Measuring has been
happening for a long
time
• Indicators have
proliferated from the
1990s onward
• Many things are
measured:
• Competiveness
• Sustainability
• Quality of life
• Civic epistemology
• Public administration is
measured and
performance is
communicated
• Track performance
• Guide policy
• Inform how cities are
governed & regulated

11. Indicators
• Quantified measures that can be tracked
over time
• Suite of related measures used for cross
validation
• Proliferation 2 agendas
• UN Conference on the Agenda 1992 – Chapter 40
Agenda 21
• New managerialism (efficient, effective,
transparent, value for money, evidence-
informed decision making)

12. Types of indicators
• Single Indicators
• Direct measures -
#social housing units,
#unemployed people
• Indirect measures –
#patent applications,
particulate matter
• Surrogate measures –
from existing data,
#renters, #homeowners
• Composite indicators
• Overall score
• Interrelated and
multidimensional
• Several weights and
measures to created a
new derived measure,
ex. Deprivation Index
• Geodemographic
indicators
• Black box, IP

13. Indicator Deployment
1. Descriptive / contextual
• Insight into phenomenon between places
• Contextual & non prescriptive or disciplining
2. Diagnostic/performance/target
• Effectiveness of a policy program
• Absolute or relative
• Causality, measure of impact
• Evidential feedback loop – new goals, interventions
3. Predictive and conditional
• Predict and simulate, forecast
• Modelling
• Predictive analytics & predictive/anticipatory governance

14. Benchmarking
• Comparing how well a city is doing vis-a-vis
another
• Scorecarding
• Competitive, aspirational – motivational
• Learning by monitoring
• Rankings can be used for place promotion
for FDI

15. Types of Benchmarking
1. Performance
• How well compared to
another
2. Process
• Comparing practices,
structures and systems
in place
3. Policy
• Outcomes & prescribed
expectations
1. Competitive
• Ranked & rated
regardless of desire to
be compared (#1 city)
2. Cooperative
• Cities participate by
sharing info but not in
direct competition
(vital signs)
3. Collaborative
• Cities work together
(FCM QoLRS)

17. Real-Time Dashboards
• “a visual display of the
most important
information needed to
achieve one or more
objectives;
consolidated and
arranged on a single
screen so the
information can be
monitored at a glance”
(Cook 2006)
• Key info to run a city
• Console for navigating
and visualizing
interconnected data
• To improve the span of
control
• Easy interpretation &
interactive
• Control rooms

18. 30 agencies, traffic, transport, emergency services, etc.

19. Indicating, benchmarking &
Dashboarding
• State of play of a city
• Objective, trustworthy,
factual data
• Rational, neutral,
comprehensive and
commonsensical view
of the city
• Monitor & evaluate
effectiveness
• Realist epistemology
2 views
1. Facilitating
empowerment,
democracy &
accountability &
transparency
2. Enacting regulation,
control, efficiency &

20. Epistemological economy
• New managerialism
• Operational practices w/ to targets
• Discipline underperformance
• Cities are knowable & manageable
systems that are rational,
mechanical, linear & hierarchical
• Technocratic rationality
• City intelligence
• Data and other info
• Indicators are one element
• The city is not a machine
• Indicators are a learning tool
Key element
toward data-
driven
evidence-based
governance &
policy
formulation &
the means to
replace
anecdote &
forms of
clientism,
cronyism and
localism

21. Comstat

22. Realist ontology
• Realist ontology
• We can know the world
through numbers
• The city as a set of
visualized facts
• Data capture the essence
of a city
• Mechanical objectivity
• Data are neutral and value
free
• Critical understanding
• Data are not independent
of the ideas, instruments,
practices, context,
knowledges and systems
used to generate, process
and analyze them
• Data are part of complex
socio-technical systems
that reflect the world and
produce it
• Part of technological
regimes

23. Data Assemblage
Attributes Elements
Systems of
thought
Modes of thinking, philosophies, theories, models,
ideologies, rationalities, etc.
Forms of
knowledge
Research texts, manuals, magazines, websites,
experience, word of mouth, chat forums, etc.
Finance
Business models, investment, venture capital, grants,
philanthropy, profit, etc.
Political
economy
Policy, tax regimes, public and political opinion,
ethical considerations, etc.
Govern-
mentalities /
Legalities
Data standards, file formats, system requirements,
protocols, regulations, laws, licensing, intellectual
property regimes, etc.
Materialities &
infrastructures
Paper/pens, computers, digital devices, sensors,
scanners, databases, networks, servers, etc.
Practices
Techniques, ways of doing, learned behaviours,
scientific conventions, etc.
Organisations
& institutions
Archives, corporations, consultants, manufacturers,
retailers, government agencies, universities,
conferences, clubs and societies, committees and
boards, communities of practice, etc.
Subjectivities
& communities
Of data producers, curators, managers, analysts,
scientists, politicians, users, citizens, etc.
Places
Labs, offices, field sites, data centres, server farms,
business parks, etc, and their agglomerations
Marketplace
For data, its derivatives (e.g., text, tables, graphs,
maps), analysts, analytic software, interpretations,
etc.Rob Kitchin, 2014, The Data Revolution, Sage.

24. Politics of indicators
• Politics in their
selection, visualization,
deployment and use
• Stakeholder led
• Community participatory
led
• Think tanks
• Principle based or
politically driven
• Data driven
• Economically motivated
• Juking the stats,
spinning, Campbell’s law
• Deep normative effect
used to shape
governance, modify
behaviour, influence
decision making
• Instrumental use
• Conceptual use
• Tactically use
• Symbolic use
• Political use
• They become a
normalized way of
thinking about and
performing governance

25. Instrumental rationality
1. Reductionist Contingent
relationships become
one dimensional
2. Decontextualizes a city
from history, political
economy, etc.
3. Longitudinal, trends,
but temporal register of
cities unclear
4. Assumption of
universalism across
place
• Zero sum game
• Dashboards can facilitate
an illusion of seeing the
total city
• Global scopic system
• Translators not mirrors
• Communication protocol
• They produce meaning

26. Technological issues
• Veracity
• Accuracy
• Fidelity
• Errors
• Bias
• Consistent
• Reliable
• Trustworthiness
• Truthfulness
• Provenance
• Modifiable areal unit
problem
• Ecological fallacy
• Classification
• Weighting – composites
• Metadata &
methodological guides

27. Power/knowledge

28. Federation of Canadian Municipalities
Quality of Life Indicator System

29. Federation of Canadian Municipalities
Quality of Life Reporting System

31. Municipal Data Collection Tool

32. Atlas of the Risk of Homelessness
“https://gcrc.carleton.ca/confluence/display/GCRCWEB/Pilot+Atlas+of+the+Risk+of+Homelessness

33. Risk of Homelessness
Indicators Across Time

34. Aging Social Housing Stock by
Neighbourhood: Toronto

35. Dublin Dashboard

36. All-Island Research Observatory
• Spatial data portal and consultancy specializing in
evidence-based planning
• Been operating since 2005 (initially as CBRRO)
• Interactive mapping & graphing modules both North/South

37. AIRO – data, maps, services

38. Partnership & Funding
• Developed (Start 2013):
• The Programmable City project
• All-Island Research Observatory (AIRO)
• Partnership:
• Dublin City Council
• Funded:
• European Research Council
• Science Foundation Ireland
• 2 years of funding (spread over 3 years)

39. The Dublin Dashboard includes:
• real-time information
• time-series indicator data
• & interactive maps about all aspects of
the city
Benefits:
• detailed, up to date intelligence about
the city that aids everyday decision
making and fosters evidence-informed
analysis.
Freely available data sources:
• Dublin City Council
• Dublinked
• Central Statistics Office
• Eurostat
• government departments
• links to a variety of existing
applications
Produced by:
• The Programmable City project
• All-Island research Observatory (AIRO)
at Maynooth University
• working with Dublin City Council
Funded by :
• the European Research Council (ERC)
• Science Foundation Ireland (SFI)

40. Why produce a Dublin Dashboard?
• To answer the following questions:
• How well is Dublin performing?
• What’s happening in the city right now?
• Where are the nearest facilities to me?
• What are the patterns of population, employment,
crime, housing, etc in the city?
• What are the future development plans?
• How do I report issues about the city?
• How can I freely access data about the city?

41. Dublin Dashboard
Logic & principles
• Provides practical, useful, accessible city intelligence to public,
government and companies to aid everyday decision making,
evidence-informed debate, and policy formulation
• Pull together data about all aspects of the city – including real-
time info - from as many sources as possible (e.g., DCC,
Dublinked, CSO, Eurostat, govt depts)
• Select data that are:
• systematic and continuous in operation and coverage
• timely and traceable over time
• Data displayed through an analytical dashboard that uses
interactive data visualisations that require no a priori knowledge
to use
• Produced as a platform that leverages existing resources and
encourages new app development.
• The data are open for others to use and re-work.

42. • How’s Dublin Doing?
• Dublin Indicators and benchmarking
tools
• Dublin Real-Time
• Real-time data from sensors across
Dublin
• Dublin Mapped
• Detailed Census maps for 2006 &
2011 Census, crime, live register
• Dublin Planning
• Zoning and planning permissions
• Dublin Near To Me
• Maps of location and nearness to
public services, area profiles
• Dublin Housing
• Maps of housing, house prices and
commuting patterns
• Dublin Reporting
• FixMyStreet, CityWatch, FixMyArea
• Dublin Data Stores
• Access to all data used in the
dashboard
• Dublin Social (in progress)
• Maps of social media activity
• Dublin Modelled (in progress)
• Modelling and scenario tools
• Dublin Apps (in progress)
• Directory of apps relevant to Dublin
• Have Your Say (in progress)
• Feedback from users

43. Dublin Dashboard - Next steps
• The Dashboard is extensive, but far from finished
• It is an on-going project and we are working on:
• adding more real-time data
• extending indicator/benchmarking data and mapping modules
• opening up more datasets and encouraging new data
generation, more geo-referencing of data, and better ways to
share data (APIs, machine-readable)
• adding new modules: city snapshot, social media, modelling
(needs investment), links to city apps
• translating for mobile platforms (e.g. tablet/smartphone
apps)
• encouraging others to leverage data and add new apps
• We’re interested in working with any interested parties
to help develop Dashboard further or to implement it for
different places

44. Open Data Indicators

47. URLs
1. Federation of Canadian Municipalities (FCM) Quality of Life Indicator
System - http://www.fcm.ca/home/programs/quality-of-life-
reporting-system/faqs.htm
2. Municipal Data Collection Tool (MDCT) http://www.municipaldata-
donneesmunicipales.ca/index.php?lang=en
3. Atlas of the Risk of Homelessness
https://gcrc.carleton.ca/confluence/display/GCRCWEB/Pilot+Atlas+of
+the+Risk+of+Homelessness
4. Dublin Dashboard http://www.dublindashboard.ie/pages/index
5. Open Knowledge Foundation Index http://index.okfn.org/
6. G8 Open Data Charter http://www.ogpireland.ie/2013/06/28/g8-
charter-on-open-data/

48. Q & A
Acknowledgements
Programmable City project research is funded by a European Research Council Advanced Investigator award
(ERC-2012-AdG-323636-SOFTCITY).
"Great cities embrace the data ... they are not defensive
about it ... they improve" Louisville Mayor, Greg Fischer