Bogotá’s transportation secretariat and the taxi-hailing app Tappsi partnered to provide valuable insight into Bogotá’s traffic patterns. Together, they reached a pioneering data-sharing agreement to provide accessible, anonymized traffic data held by Tappsi on approximately 15,000 cars, at no cost to the city, giving the city a new lens for analyzing transit need.
Formulating responsive and effective public policy requires access to good information. In our era of big data and ‘digital exhaust,’ there are incredible opportunities to identify resident needs and preferences and to monitor services in real time. However, managing that information has become exponentially more complex. In addition to legal, technical and financial hurdles, there are new political trade-offs. The way that a city government confronts (or skirts) issues such as data privacy, ownership and access can have profound implications for trust and democratic representation.
How’d They Do It?
"The fundamental input you need to plan a city is the information about how people travel and where they travel to,” said Transportation Secretary Andres Archila. Prior to this initiative, Bogota’s data-gathering process was slow and ineffective. The city wanted to step up its traffic management and create a smooth, integrated transportation system. A visit to Korea for a data conference sparked the idea to access private taxi data, but the journey from a common-sense idea to an implementable policy was long.
The experience demonstrated that cities don’t necessarily need money to innovate, just creativity and an experimental approach. And launching small experiments or seizing the ‘adjacent possible’ can be a low-risk way to tackle otherwise daunting new projects. For Bogota, obtaining an available, ‘off the shelf’ data resource at no cost has provided an on-ramp to begin building new technical capacities, modernizing planning processes and updating legal frameworks around a core city service.
How’s It Going?
The Secretariat considered other uses of the Tappsi data, such as better targeting messages for the Secretariat’s Yo le doy ritmo a Bota (I give rhythm to Bogota) campaign, which seeks to reduce gridlock caused by cars ‘blocking the box.’ The data could also be useful in planning alternative transit. The Secretariat hired a ‘Bike Czar’ to coordinate all of the City’s efforts to encourage bicycle usage, including a planned 25 km bicycle highway, safety programs and community outreach to cyclists.
Updating legal frameworks
Often, pre-existing laws governing information management cannot easily accommodate novel data-sharing partnerships. In Bogota, there was no precedent to follow.
Achieving data compatibility
Free data obtained ‘as is’ is not necessarily compatible with government systems, and could incur significant resources to process.
Moving from data to information
After resolving issues with data access and compatibility, Bogota still had to grapple with how to extract useful, policy-relevant information from the data. They call this the challeng of squeezing “el jugo” from the data.
Managing the public perception
- Trust - Bogota officials feared a backlash from citizens suspicious of private-sector involvement, including the potential for companies to receive unfair benefits or privileges. They recognized the need for confidence-building measures, including transparency around the terms of the collaboration.
- Openness - Bogota’s agreement does not open Tappsi’s traffic data to the public, a tradeoff that mitigates trade-secret and privacy concerns but could undermine citizen confidence in policy decisions. It also forecloses the possibility of third parties helping to squeeze ‘el jugo’ from the data.
- Fairness - Selecting one vendor’s data could raise concerns that the government is intervening in a competitive market, absent a fair and open process to select the private partner.
- Privacy - Anonymizing Tappsi’s data was important to ensure that the transit habits of individual users would not be exposed.
As data begins to inform and drive public policy decisions to a larger and larger extent, questions about its provenance and processing become more important. Are populations occupying ‘data deserts’ invisible to city planners? What assumptions and biases are built into data collection and analysis, and who makes key decisions about data collection and usage?