Join us at the upcoming Portland Tech Jam ’19 where we’ll present our forthcoming paper that addresses Smart Cities privacy and innovation challenges with pragmatic policy-informed technology solutions: Look for the full article in the ACM Conference Proceedings (Isaac Potoczy-Jones, Erin Kenneally, John Ruffing, “Encrypted Dataset Collaboration- Intelligent Privacy for Smart Cities, SCC’19, September 2019, Portland, Oregon USA). In summary:
The past year has seen increasing scrutiny of Smart Cities efforts with regard to privacy. Privacy advocates have criticized Smart City data collection on the whole and critiqued specific city efforts that they feel have crossed a line.
Cities are struggling with a number of privacy issues, including how to address third parties’ collection of Smart City data, how cities consume personally identifying information from third-parties, and how public records laws intersect with privacy concerns.
The majority of data that cities collect are subject to disclosure under public record laws, with an attendant obligation to anonymize sensitive private information. However, as the amount and availability of data increases, the ability to cross-reference, correlate, and de-anonymize or re-sensitize datasets also increases. This leads to re-identification attacks that infringe the privacy of individuals in those datasets, and fosters mistrust in city governments and technology vendors. A fundamental challenge is that open data and privacy interact in complex and unpredictable ways. Some cities may choose to allow third parties to collect and manage that data in an effort to encourage innovation in the delivery of city services, while simultaneously wrestling with the legal and policy implications, such as privacy and public records law compliance. Unfortunately, this also may have undesirable privacy outcomes depending on a third-party’s use of that data and the city’s role in encouraging its collection.
In this paper, we will discuss concrete approaches to smart cities data privacy governance including collection and management, and specifically, an innovative pilot project supported by the U.S. Department of Homeland Security, Science & Technology Directorate aimed at demonstrating how privacy technology can help harmonize data sensitivity risks with intended benefits.
Streaming data presents a different problem from query/response.
These are streaming projects for city data, showing what is possible when you make valuable city data available in real time. The current projects in this repository are: All projects proxy city data using Streamdata.io, and uses Server-Sent Events (SSE) to push updates to each existing city data JSON API, only sending what changes using JSON Patch.
Should Data Exchanges be based on free or open data? As many of you may know, Open is different from Free. Open software, for example, refers to reading software source code. Free software allows you to use the software for free. Data can be Open or Free, or both.
We discuss the cost of providing Free data in a world where more and more data is being produced. New business models are evolving for Open Data that encourage use, innovation, and business model development and preserve the rights of innovators and data users as well as those who provide the data.
When it comes to smart city innovation, it’s arguable that most use cases are not that exciting to the average resident. A connected garbage bin, traffic light or parking meter is not going to cause applause and adoration for city officials at least in the first instance.
Open Data Policy – Managing Information as an Asset
The Federal Open Data Policy states: “Agencies must apply open licenses, in consultation with the best practices found in Project Open Data, to information as it is collected or created so that if data are made public there are no restrictions on copying, publishing, distributing, transmitting, adapting, or otherwise using the information for non-commercial or for commercial purposes.””