Works Exploring the question: what's next for Milan's Expo area?
Oxway

Exploring the question: what's next for Milan's Expo area?

Client benefit

Public Education & Information - Visualize qualitative research for the general public

Project objective

Visualize the alternative proposals and popular vote results of a qualitative public opinion study on what to do with the spaces of the Milan EXPO area after its conclusion.

Project results

An innovative and engaging way to present and communicate the survey results allowed public opinion to influence the fate of the space, while supporting public understanding of what the favoured alternatives were.

Project background

Upon conclusion of EXPO Milan, Italian newspaper Corriere della Sera commissioned Oxway to conduct a survey to identify citizen's preferences regarding the future use of the EXPO area.

The data application pulls in qualitative data based on an analysis of open-ended survey questions that organizes them into topical clusters according to the kind of proposal and sociodemographic criteria. With this visualization, users can explore and analyze each of these answers to determine the public preference for the future of the EXPO Milan area.

Explore the project

Visualization of the proposals and vote results of a public opinion study on what to do with the spaces of the EXPO area after its conclusion.

Oxway data-analyisis dashboard overview

The interactive dashboard


Users can explore and analyze each of these answers to determine the public’s preference for the future of the EXPO Milan area.

We designed an interactive application which allows the user to explore and analyze every single open-ended response through organization of answers into topical clusters according to socio-demographic criteria.

Oxway dashboard circle detail

The visualization module


Every circle represents each one of the 977 proposals.
Its position relates to its affinity with one or more of the 5 macro-categories.

Detail on the filter

Filtering the view


Results can be filtered through different parameters.
The data complexity is then translated into a color scheme.

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