Urban data governance and policies : a comparison using case studies

Due to increasing internet access and mobile phone usage, the collection of data has exploded globally in the past decade. At the same time, the processing power and storage capabilities have become cheap and prevalent, and sophistication and complexity of AI and machine learning algorithms have advanced and are widespread. Data is a new type of capital. Public governance has not yet caught up, and because of the specialized technical expertise required, the public sector has permitted and sometimes even invited private companies to make the rules. Caught up in these trends is a tension between cities wanting to be at the forefront of technology while needing to act in the public interest and protect the marginalized and underrepresented. This thesis utilizes a comparative analysis of two case studies, Toronto and New York, to examine the existing urban data governance models and identify some learnings from the comparison. Within each case study, the thesis employs systems architectural concepts such as stakeholder mapping and architectural decisions to illustrate differences and highlight shortcomings and potential recommendations to address in future policy proposals.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering and Management Program

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Chan, Shelley (Shelley Claire)

Advisor dc:contributor.advisor

• Jason Jackson and Joan S. Rubin.

• Engineering and Management Program.
• System Design and Management Program.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/132808

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/132808