The presentation discusses lessons learned from the Programmable City Project, focusing on open data and homelessness systems in Dublin, Ottawa, and Boston. Key findings highlight how data cultures shape open data practices and the political economy surrounding homelessness, while emphasizing the need for better integration of administrative data in smart city frameworks. The conclusion calls for a responsible understanding of socio-technological assemblages to effectively govern cities and balance various societal needs.

1. progcity.maynoothuniversity.ie
Presentation #2:Open/Big Urban Data
Lessons Learned from the Programmable City Project
Mansion House, Dublin, May 9th, 2018
10am-2pm
http://progcity.maynoothuniversity.ie/2018/03/lessons-for-smart-cities-from-the-
programmable-city-project/
Dr Tracey P. Lauriault
Assistant Professor, Critical Media and Big Data
School of Journalism and Communication
Carleton University
@TraceyLauriault

2. 1. Summary of research
3 Case studies
• Open Data (Canada, Ireland)
• Homelessness Intake Systems (Dublin, Ottawa, Boston)
• Data Model Ordnance Survey Ireland

3. 1.1 Socio-technological Assemblage (Kitchin 2014)
Material Platform
(infrastructure –
hardware)
Code Platform
(operating system)
Code/algorithms
(software)
Data(base)
Interface
Reception/Operation
(user/usage)
Systems of thought
Forms of knowledge
Finance
Political economies
Governmentalities legalities
Organisations and institutions
Subjectivities & communities
Marketplace
System/process
performs a task
Context
frames the system/task
Digital socio-technical assemblage
HCI, Remediation studies
Software studies
New media studies
Game studies
Critical Social Science
Science Technology
Studies
Platform studies Places
Practices
Flowline/Lifecycle
Surveillance Studies
Critical data studies
Critical code studies
AI/Machine Learning

4. 1.2 Modified Dynamic Nominalism (Hacking)

5. 1.3 Genealogies (Foucault)

6. 2. Key findings
2.1 Data cultures and technologies shape open data
practices

7. 2.2 Political Economy of Homelessness
Ottawa, Canada
Homeless Individuals &
Families Information System
(HIFIS)
Dublin, Republic of Ireland
Pathway Accommodation and
Support System (PASS)
Boston, US, Homelessness
Management Information
Systems (HMIS)

8. 2.3 OSi Data models
• GeoData models represent material reality but that is
mediated by people and their knowledge

9. 2.3 OSi Data models
GeoData Models – echo the past, reflect each other and are built
on earlier models and new features in the world

10. 3. Key lessons
• 3.1 Open Data as a institutional practices is not mapped
across institutions and practices, esp. the smart city

11. 3.2 Homelessness Intake Systems
• Counting needs to be integrated into larger political and
economic processes, smart cities do not see these kinds
of administrative data

12. 3.3 OSi Data Model
• The change over between old and new technologies
have social and material effects

13. 4. Conclusion
Data and Technology are social, technical and political
artifacts, than are more than the unique arrangement of
objective and politically neutral facts & things
that do not exist independently of ideas, techniques,
technologies, systems, people and contexts regardless of
them being presented in that way.

14. We live in a technological society that is data driven,
and to be responsible technological citizens we need to
know about socio-technological assemblages so that we
may act as agents to better mobilize data and
technologies when warranted in an ethical, accountable
and transparent way to govern cities as a fair, viable and
liveable commons and balance economic development,
social progress and environmental responsibility
for all of us.

15. Tracey.Lauriault@Carleton.ca
@TraceyLauriault
https://carleton.ca/sjc/profile/lauriault-tracey/
progcity.maynoothuniversity.ie