Public Spaces #DataCity #AMS

How can urban data be used to reinvent public spaces? How can public spaces be redesigned in response to the needs of citizens? These were the questions explored this past 23 June by the Amsterdam Institute for Advanced Metropolitan Solutions (AMS) and La Fabrique de la Cité (partners since March 2016), at a “Public Urban Squares” workshop in Amsterdam’s FabCity.
The workshop specifically examined the examples of Paris’ Place de la Nation and Amsterdam’s Weteringcircuit. Dutch and French experts (City of Amsterdam, Delft and Wageningen Universities, NUMA, etc.) examined the role of technology and innovation in designing and improving public spaces. Participants learned about the results of the DataCity initiative, a competition launched in November 2015 by the City of Paris in collaboration with start-up accelerator NUMA. Nicolas Enjalbert (Innovation Programs Manager at NUMA) presented the experiment conducted by start-ups Qucit and Padam, both accelerated by DataCity.

Qucit: using urban data to redesign public spaces

Place de la Nation is among the seven Parisian squares that Paris has decided to redevelop. But the design of a public space cannot be updated without a thorough understanding of the uses made of the said space by the city’s inhabitants. This is at the heart of the work conducted by Qucit, which focuses in predictive analytics as applied to urban mobility.
In partnership with Cisco, Qucit installed sensors on Place de la Nation and gathered dynamic data on air quality, noise, and pedestrian traffic patterns over the course of several weeks. This dynamic data was then crossed with static data (location of trees and street furniture, spatial configuration, etc.), open data (weather, traffic) and the results of a survey of passers-by. Qucit then used this data to create a user comfort index based on multiple criteria: ease of movement/orientation, cleanliness, sense of security, beauty of the surroundings, etc.
The project aimed to better understand user behaviors and experiences with Place de la Nation, to identify factors which affect this experience, and to pinpoint relevant correlations (e.g., the relationship between pedestrian traffic density and stress levels). Qucit’s work has allowed for the construction of a predictive model of user comfort in the public space. This innovative data will be made available to urban planners to help them quantify the impact of urban redevelopment measures. But data collection on individual practices in public spaces is also a way for inhabitants to reclaim these spaces, as they become involved in redesigning them.

Padam: experimenting with on-demand buses to improve short-distance mobility

Padam, the start-up selected by DataCity to work on short-distance mobility, has developed a system of shared, on-demand minibuses that users can order using a mobile application. Tested on a limited scale within Paris’ 19th arrondissement, where operating micro-bus lines has proven costly and at times inefficient, the plan implemented by Padam, with help from VINCI Energies, is designed to optimize public transport options in underserved neighborhoods.
The project will help achieve a better understanding of the differences in efficiency, logistical operation and costs between fixed and on-demand bus services. Although the experiment conducted in the 19th arrondissement has come to an end, other underserved areas will now be identified, where Padam’s proposed solution is likely to become an attractive alternative to existing options.
This first edition of DataCity initiative has succeeded in bringing private and public stakeholders together to work toward urban innovation by combining start-ups’ data-related technical expertise with the broader vision of urban planners and public actors.
In the coming months, AMS and La Fabrique de la Cité will continue to work towards designing and improving public spaces by formulating collaborative proposals based on their experiences in Paris and Amsterdam.

• Amsterdam Institute for Advanced Metropolitan Solutions