Project Info

Team Name

IDeEA lab

Team Members

2 members with unpublished profiles.

Project Description

Engaging with local community through playful visualisation of (geo-located) city data as parametric interactive abstract faces. Developing a mobile AR (Augmented Reality) app with two modes, where ‘Mode 1’ will be - translating city data as a parametric face of the city (neighborhood) and ‘Mode 2’ will enable the application of this city ‘FaceMap’ as a live selfie effect using Face Tracking AR technology.

Each year Australian government collects tons of potentially useful and interesting data. However most this data lays dormant and is not being utilised, because most of the data is being collected, stored and communicated to public as those ‘boring’, hard to read spreadsheets or text files.

The fact is that not all people are good at reading numbers and/or understanding and interpreting numeric or text-based data sets. Thus, en masse, public is reluctant to actively engage with this potentially valuable source of information.

However humans are really good at reading faces and facial expressions. We use our faces to communicate complex information - instantly. It’s in our human nature. We wake up in the morning and we look in the mirror. What does our face tell us? Throughout history portraits played a crucial role in art and culture. We see faces on book and journal covers, advertisement and movie posters. Nowadays - selfies are integral to social culture. AR Face Tracking technology is extremely popular among available mobile apps, and live selfie effects (such as snapchat filters) are being used daily by millions of people (Snapchat alone is used be over 158 million people daily).

Make data visualisation - engaging and easy to ‘digest’!
Use data variables as generative face attributes.

Data Story

This projects taps into human natural capabilities of reading and understanding faces. The intent is to translate geo-located city data as (hopefully cute and engaging) abstract faces, allowing people to use the city ‘FaceMaps’ as selfie effects or view them as a combined map of data-faces [What is the face of your city?].

FaceMap prototype uses following data to visualise the "faces" of cities:

-Total Population
-Median age
-median taxable income
-Average Taxable Income
-Median Rent (weekly)
-Average Household Size
-Total Private Dwellings
-Dwelling With No Motor Vehicles
-Education: Bachelor Level and Above
-Average Total Business Income
-Average Net Tax

-Age of community (young-old)
-Homeowner status (renting / paid in full / paying the home loan / etc.)
-Occupation (student / working full time / unemployed)
-Park (green) area in the city
-Education level
-Population density
-Health level
-Houses water consumption
-Houses energy consumption
-Average income
-Number of sport facilities / public libraries / art centers

Output 1:
Mobile app generating an abstract face interpretation, where facial attributes are informed by local city data, including such data variables as: average age of community, homeowner status, occupation, park (green) area in the city, health level, sustainability of housing: energy and water consumption, average income, education level etc…. And allowing people to express and share their feeling and emotions regarding the current state of city ‘FaceMap’ by choosing happy/unhappy facial expressions that will be applied on this data-face-interpretation.

Outputs 2:
Mobile selfie effect app, which would apply chosen various city faces as masks, using Face Tracking AR technology. Allowing people to share these FaceMap selfies with the larger community, raising public awareness of current state of Australian cities.

Evidence of Work



Team DataSets


Data Set


Data Set

DSS Demographics

Data Set


Description of Use data of different cities are downloaded to generate "faces"

Data Set

Challenge Entries

Helping the community realise we’re in their corner!

Local Government has lots of data, so how can we utilise the data we have, and the open data out there to tell the story of what we do, how we do it so well, and how this benefits the community, in ways that constituents will receive and understand?

Go to Challenge | 11 teams have entered this challenge.

Telling Stories with Data(.Vic)

Accessing any of the datasets on data.vic, this challenge asks participants to extract and tell stories from data. Alternatively how might we facilitate citizens’ own inquiries and investigations via the Victorian Government Open Data Portal?

Go to Challenge | 21 teams have entered this challenge.

Bounty: Integrating AIHW

How can we integrate AIHW and other data sources in interesting ways?

Go to Challenge | 28 teams have entered this challenge.

Show Us The Numbers

How can we use open finance data to turn numbers into stories?

Go to Challenge | 13 teams have entered this challenge.

Bounty: Visualise the Numbers

How can people better view data on GovCMS in visuals?

Go to Challenge | 10 teams have entered this challenge.

Bounty: Mix and Mashup

How can we combine the uncombinable?

Go to Challenge | 61 teams have entered this challenge.

Activate Melbourne - A Prosperous City

This challenge aims to simplify the steps taken to decide where a new business could be located, or where there is underutilised space in the city.

Go to Challenge | 10 teams have entered this challenge.

Growing Wyndham

This challenge aims to develop innovative new ideas to help plan for Wyndham as a growing city. Winning entry will be a best concept/product that is useful for the people of Wyndham.

Go to Challenge | 15 teams have entered this challenge.

Australians' stories

What meaningful ways can we tell the story about what it's like to be an Australian, and in what ways some Australians live very different lives than others? How can we make people more aware of the issues facing themselves and others as they go through life?

Go to Challenge | 34 teams have entered this challenge.