Urbanism Next
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Working with Data

Obtaining, understanding, and effectively using data can help us understand how emerging technologies are changing mobility.

Data is the new frontier for transportation planning. The wealth of data being collected by both public and private transportation providers brings new opportunities for understanding and adapting to transportation trends. Private companies collect data in part to better understand their business operations and increase their competitiveness. Public agencies need information about what is happening in the public right-of-way to ensure the health, safety, and welfare of residents and visitors. Accessing data, being able to process and synthesize it, as well as understanding how to interpret and act upon it are all potential hurdles in having a data-driven transportation planning process.

Issues & approaches

Data Accessibility: Private companies are not always forthcoming with their data. The data private companies collect is a valuable asset for them. Further, many private companies cite privacy concerns as a reason for not wanting to share data. One way for public agencies to ensure they get the data they want/need is to require data reporting in permits/operating regulations of TNC and micromobility operators. The Open Mobility Foundation, a consortium of public agencies and private companies, is working on addressing issues of privacy and best practices. The Drivers Seat Cooperative is another organization that works to get data into the hands of gig drivers.

NACTO and the International Municipal Lawyers Association (IMLA) published guidance in 2019 on Managing Mobility Data and identified four principles for managing data including: It should be for public good, it needs to be protected, it should serve a specific purpose such as “planning, analysis, oversight, and enforcement”, and it should be portable with open standards and formats.

Data Processing: The amount of data gathered by private transportation providers is vast, and more isn’t always better. Not only can mountains of data overwhelm both staff and computing capacities of many public sector offices, but the array of data types can obscure the most important results. The Mobility Data Specification (MDS), pioneered by the Los Angeles Department of Transportation, created a standardized way for public agencies and private agencies to collaborate and exchange and analyze data. The Open Mobility Foundation now leads efforts to promote MDS.

Data Privacy: The widespread use of smartphones allows for unprecedented tracking of people’s movements and search history, collected by both private companies and public agencies. A wide variety of academics and others have concerns about surveillance capabilities and how that information will be used. Public agencies need enough information to be able to make informed decisions, while protecting an individual’s identity and movement. Even trip data without information about an individual has been combined with geo-location data to be able to identify individuals. Public agencies and private companies should regularly update and adhere to best practices to protect individual privacy.  

Data Storage: Understanding data storage requirements and how public records requests apply to transportation data obtained from the private sector are important considerations for public offices. Private companies that make raw or aggregated data available for purchase may have stipulations that prevent anyone other than the original purchaser from accessing the data. Similarly, data obtained directly from private transportation providers may contain information deemed to be trade secrets that also cannot be shared. With aggregated or anonymized data sets, often the data are so rich that individuals may be able to be identified despite anonymizing. All reasons to be careful with data storage and to understand how and when public records requests may apply.

Examples/case studies

Los Angeles Data Protection Principles

View - City of Los Angeles

The City of Los Angeles created the Mobility Data Specification (MDS), a system for easily sharing data between private companies and public agencies. This press release contains an overview of MDS's data protection strategies.

SharedStreets Micromobility Data Processing Pipeline

View - SharedStreets

This is a tool public agencies and research organizations can use to interpret MDS data.

Data on Demand: A Case Study in the Los Angeles and Puget Sound Regions

View - Eno Center for Transportation

This report details an an example of public and private sectors using robust data requirements to evaluate transportation projects.

Related topics

Micromobility

From established bikeshare programs to emerging scooter share systems, micromobility is encouraging active transportation.

Transit

Transit is the most efficient way of moving people, but many transit systems are facing challenges. What happens when AVs arrive?

Equity

How will the impacts of emerging technologies impact vulnerable and low-income populations? What opportunities are there to improve services and reduce inequities?

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