Australian Taxation Office

Government Agency Supporter

Our Prizes

Data Intelligence Hack (Data journalism, spatial modelling, analytics) (Major Prize)

This category is all about using government data to optimize business decisions.
What data intelligence can you derive from official data that would be of value to a business? Can you help industry plan, predict or model future perspectives? Perhaps you can build a tool that helps startups understand the available data and make better business decisions? Maybe you have an idea that will help business solve a problem.

Smarter Data (Bounty Prize)

The challenge is to find new ways to interrogate the ATO Dataset and help people with little or no statistical background better understand the effect of ATO data on other things. In particular you should look at ways to identify weak signals caused by tax data in other data sets where the impacts are first seen somewhere other than in the Tax data BUT are caused or heavily influenced by, the existence of that data. Hint: Ask yourself questions like : What’s the social impact of financial hardship? How do lifestyle factors impact income levels and wealth generation? What’s the impact of education spending on incomes, What links can we identify between unemployment, income and marriage separation? How useful are the SEIFA regions as indicators of taxation impacts?

Our Mentors

Anthony Nolan

Innovation Officer / Data Scientist / Intelligence Analyst

Daniel Grbac

Information Designer

Dave Kuhl

Director, Operational Analytics

David Spatcher

Director, Enterprise Analytics

Jenny Coppock

Business Development Officer

Josh Parry

Assistant Director

Michael Tran

Comunications officer

Nandita Sharma

ICT Specialist Consultant

Peter Tunnacliffe

Intelligence Analysts

Robert Williams

Senior Data Miner

Stewart Turner

Senior - Intelligence Analyst & Data Analyst

Our Featured Datasets

Taxation statistics - Aggregated individual tax return sample files

The de-identified data from the 2013-14 individual 2% sample file ( has been aggregated to the following levels: Sex Age (5 year ranges) Occupation (1 digit level) Partner Status Location (SA4 Region name) Lodgment channel...

Taxation statistics - Individual tax return sample files

A series of sample files of individual tax return information for more advanced users. These files are confidentialised in order to protect the identities of taxpayers. The files contain a 1% sample of records for 2010-11 and earlier income years, and a 2% sample of records for the 2011-12 inc...

Major National Sponsors

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