Local and federal governments have significant amounts of data that they have opened for public use. We know that currently, these datasets are gold mines to provide unbiased education of young people on the world they live in, but aren’t accessible in a fun or even simple manner. In fact, they often require significant understandings of data analysis to make sense of.
Correlation Explorer is a website that allows users to find trends between different data variables from open data. For the purposes of this challenge, users can upload their own datasets to find correlations on our graph. In the future, our recommended datasets will also be uploaded for use.
As seen by the success of a viral correlations website (Spurious Correlations), the first step to engagement is creating something people want to engage with; something fun and user friendly. This can benefit young people looking for some fun relationships; for example, while building this program we found correlations between number of dentist practices and child protection services, as well as number of liquor licences and kindergardens. However, this data can also expose and quickly validate important issues; we found correlations between Indigenous populations and unemployment, as well as single parents and decreased personal incomes.
The possibilities of datasets used are endless, and we encourage local governments to send in their own data. In the future, we aim to upload a large dataset for the user’s use, and to add interesting information on each variable below the graph. The room for future education is infinite; the first step is to engage.
To create and test this program, we merged multiple datasets including the 2011 Town and Community Profile Data, the Yoga Pilates and Tai Chi in Victoria, as well as the Liquor and Gaming License, and created a large single dataset to test and track correlations.
Evidence of Work
Yoga, Pilates and Tai Chi in Victoria
Description of Use: This data set was brought into a comparison of Victoria data with the Town and Community Data.
2011 Town and Community Profile Data
Description of Use: This was our main dataset that we connected with all other dataset. We used the 'Community Name' to connect the town names with any data set to combine the use of data within and outside of Victoria.
Community Services (NSW)
Description of Use: This was used as extra data to put into the correlations application to see what works between NSW data and Victoria data.
Liquor and Gaming License
Description of Use: This dataset was used to connect with the main dataset we used 'Town and Community Profile'. We used this data to connect the information of liquor license registrations around Australia and compared its correlation with added from any other dataset.
Check back here once the first checkpoint passes to see the challenges this team has entered.