Between Points is a mapping experiment that visualizes the relationship between people, places, and stories through the eyes of those who drive its streets every day.
We interviewed four Uber drivers and asked each to share their three most common tourist drop-off destinations in Oakland, California. During each ride, we were dropped off at one of their top tourist spots and spoke with the driver about their experiences, listening to how they described the city through their daily routes. We also captured a memorable quote from each ride.
The collected data was then mapped to show how local knowledge and lived experience create invisible patterns of movement across the city.
Concept
Between Points explores how human stories can improve the way we visualize movement in a city. Through conversations with Uber drivers, the project reveals how their local knowledge creates a living network of routes and destinations. The goal is to reimagine the map as both a tool for navigation and a reflection of human experience.
Problem
Human Dataset
Four drivers, four perspectives, one city seen through different routes The interactive visualization maps each driver’s journey starting from California College of the Arts (Oakland), connecting to their most common tourist drop-offs. Each route reveals a different layer of how locals experience the city, creating a collective “social map” of the Bay Area.
Application Idea
A conceptual Uber Maps feature that blends driver insight with navigation, connecting efficiency with local experience.
Information Architecture:
Future Application with Local Layer Concept:
Reflection
This social experiment project taught me that mapping is not only about precision but perspective. It challenged me to balance clarity with spatial awareness and to see technology as a medium for human connection. This approach continues to shape how I combined design systems thinking with storytelling.
Takeaways
Bridging data and narrative: How design can reveal invisible human networks. Reframing efficiency: Seeing mobility as a shared experience, not just movement. Scalability: Potential to integrate driver insights into urban analytics or tourism mapping.