Table of Contents
- Introduction
- Definitions
- Principle 1. Create Processes for the Affected Community to Participate in Making and Modifying the Rules Around Data.
- Principle 2. Develop an Effective System for Monitoring to be Carried Out by the Community.
- Principle 3. Provide Accessible Means for Dispute Resolution, Use Graduated Sanctions Against Rule Breakers, and Make Enforcement Measures Clear.
- Principle 4. Promote Responsibility for Data Governance Among Multiple Layers of Nested Enterprises.
- Appendix 1
Definitions
Before we jump into the principles, let’s lay down a few key definitions.
What Do We Mean by “Smart Cities”?
A smart city uses information and communication technologies to increase operational efficiency and effectiveness, share information with the public, and improve the quality of services. To achieve these aims, cities deploy technology across various parts of city infrastructure. These technological systems use distributed sensors to collect data about the environment and city operations; centralized or embedded computing power to process that data; and actuators to manipulate urban infrastructure and adjust city operations. The smart city transforms the city into a large socio-technological system that “senses, thinks, and acts.”
Dubai, London, and New York City are pre-existing cities that have become “smart” over the last decade. Their mayors and/or governments prioritized digital transformation and technological innovation, allowing these cities to become incrementally smarter through different initiatives rolled out by various city departments atop existing infrastructure.
Other smart cities were built from the ground-up,including Songdo, South Korea, a joint venture by Cisco and real estate developers, and the Quayside neighborhood in Toronto, which is partnered with the Google-owned Sidewalk Labs. What distinguishes these from the examples above is that “the data-gathering infrastructure [is] more or less built into the walls,” and done under one cohesive strategy, rather than in piecemeal developments.
What Do We Mean by Smart City Projects?
In this primer, we refer less frequently to smart cities as a whole, than to “smart city projects or initiatives.” This is because we are speaking to any city government or department wanting to implement smart city technology, regardless of whether the city itself is considered a smart city. A city that is just now beginning its journey to becoming smart may actually benefit most from this guide, as it can learn from the experiences of other cities and build correctly from the beginning.
An example of a smart city project is the installation of networks of sensors that measure temperature, humidity, noise pollution, trash levels, energy consumption, traffic flow, and the location of gunshots. These sensors might automatically dim street lights, notify garbage collectors of full trash cans, indicate vacant or occupied spaces on parking meters, or share information on road closures or pollen counts on smartphone apps.
Other examples include deploying a mesh network, rolling out gigabit internet, and providing free Wi-Fi hotspots throughout a city. Some projects involve installing software to perform automated facial recognition or license plate recognition, or include an integrated data center that aggregates existing data from multiple sources into a single facility for monitoring and analysis.
Examples of Smart City Projects:
- Chicago: Network of sensors
- The Array of Things (AoT) project comprises a network of sensors installed around Chicago street furniture (i.e., lamp posts, traffic lights) to collect real-time data on factors impacting the city’s livability, such as climate, air quality, and noise. This data is published openly for research and public use. The project was funded by a $3.1 million grant from the National Science Foundation, and implemented through collaboration between the city and researchers at the University of Chicago and Argonne National Laboratory. About 130 sensors were deployed in late 2019, with a plan for installation of 150 sensors by mid-2020.
- New York: Free Wi-Fi hotspots
- The LinkNYC project replaces phone booths around the city with kiosks that provide free Wi-Fi and phone calls. Announced by the Mayor’s Office in 2014, LinkNYC is now built and managed by the private consortium CityBridge (made up of Qualcomm, Intersection, and Comark), which invested an initial $200 million needed to build out the infrastructure. It is free and funded by selling ad space on kiosks. However, both the media and nonprofi have raised privacy concerns.
- San Diego: Facial recognition technology
- San Diego’s TACIDS facial recognition sof was developed by the San Diego Association of Governments in 2012, receiving $100,000 in funding from the U.S. Department of Justice. TACIDS utilizes a network of 1,300 smartphone and tablet cameras, as well as a database of 65,500 face scans, for law enforcement use. Described by the California ACLU as “flawed and dangerous,” the system was shut down after 2019.
What Do We Mean by “Smart City Data”?
“Smart city data” is data collected by sensors and other technologies deployed in a smart city project, as well as the insights derived from this data.
What Do We Mean by the “Governance” of Smart City Data?
Data governance is not simply data management, or requirements on the collection, use, sharing, retention, and disposal of data, which is codified in data-privacy laws, like the General Data Protection Regulation (GDPR) in Europe and Health Insurance Portability and Accountability Act (HIPAA) in the United States. We view governance more broadly to include questions around who is making these rules and what processes are used in rule making. Our suggestions do not concern the substance of rules around collection, use, sharing, retention, and disposal of data, but rather focus on how these rules are made, disputed, and changed.
Our principles are complementary to existing substantive standards around data protection, by providing a procedural component to advance similar goals.
A final note before jumping in: Under each principle below, we describe the range of solutions that may work in any given environment. We encourage you to pick and choose options which would work based on local conditions, as community-unique characteristics will make some more effective or politically feasible than others.