Looking into societal challenges that can (partially) be addressed by using data sources, this project connects researchers to urban neighbourhood initiatives and citizens. As a collective, participants come up with solutions for these urban challenges and attempt to create feasible prototypes for addressing the issues at hand in their environment.
Stage of the project
The results of the project so far
A pilot Data Empowerment Design Studio in the city of Rotterdam focused on 'last mile delivery', i.e. the final part of the parcel delivery process from order to warehouse to a buyer's home. Participants were asked to figure out how the rise of online shopping and parcel delivery affects their personal lives and/or their living environment, and looked into possible neighbourhood-focused initiatives that could 'tweak' these developments into concepts or ideas that could enhance the neighbourhood.
What are specific, distinctive, strong elements in this project?
The project looks at global/national developments in the datafied society that affect local neighbourhoods, and involves citizens and small business owners in its attempts to 'flip the system'. The Data Empowerment Design Studio is meant to help citizens figure out how they can put data developments to their advantage. While data is usually seen as a means for upscaling, this initiative brings the technical developments back to a level that individual citizens can grasp – their everyday lives.
Which specific lessons, do's and don'ts would you like to share? What would be suggestions for others when preparing or implementing the project in their own city?
Neighbourhood collectives/initiatives have a very clear overview of topics or developments that appeal to citizens and should definitely be involved in programmes on a neighbourhood level.
Although data plays a central role, it might be wise to look into broader issues first, look into how these could be addressed and which factors play a role in citizens' everyday experience, before actually addressing the various ways in which data could be used to support these new ideas.
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