Within these pages, readers will find information related to the integration and management of crowdsourced data. Crowdsourced data include active data generated through the use of social media apps (e.g., Waze, Twitter), as well as passive data collected via cell phones (e.g., probe speed data, traveler behavior), transponders (e.g., E-ZPass, freight), and vehicle systems (heavy breaking, wiper on/off, CVs). Crowdsourced data have tremendous potential to offer new insights; however, the volume and speed at which these data are generated are unprecedented. To handle these “big data,” modern, flexible, and scalable methods to manage these data must be adopted by transportation agencies if the data will be used to facilitate better decision-making. 

Currently, the most common applications of crowdsourced data are traveler information and incident management; however, agencies are expanding use in areas such as traffic signal timing, maintenance, road weather, and work zone management. The major barriers for agencies seeking to more effectively use crowdsourced data include understanding and assessing the quality of the data, storing and managing the large amount of data, and turning the data into information to support operational decision-making. In some cases, agencies struggle to make the business case for purchasing or using the data because management does not fully understand the potential benefits of the data.

08-119 Research Products:

Demonstrate Use and Value of Crowdsourced Data Integration

For NCHRP 08-119, the team is developing a series of four guidance documents that will compile and present the challenges, lessons learned, steps taken, and recommended actions when integrating and using crowdsourced data. Each of these four documents, developed sequentially, will focus on a different type of crowdsourced data. It will also center on many real-time and archived uses of that data, either independently or through integration with other data.

Additional Resources:

EDC-5 Crowdsourcing for Operations

Crowdsourcing turns transportation system users into real-time sensors on system performance, providing low-cost, high-quality data on traffic operations, roadway conditions, travel patterns, and more. When combined with traditional data, crowdsourcing helps agencies implement proactive strategies that improve incident detection, traffic signal retiming, road weather management, traveler information, and other operational programs.

NCHRP Research Report 952 Guidebook for Managing Data from Emerging Technologies for Transportation

This guidebook for state DOTs contains over 100 recommendations for managing data from emerging technologies, such as crowdsourcing, in a modern way. It also contains a roadmap for implementing the guidance, as well as several tools including a modern data management capability maturity self-assessment. This guidebook is a good resource for agencies grappling with how to manage new, large datasets, including crowdsource data.