Data visualisation: understanding and conveying information more effectively
"The greatest value of a picture is when it forces us to notice what we never expected to see."
John Tukey (1915-2000)
Data visualisation techniques like graphs and diagrams have been used to help us understand data and information for centuries. Good visualisation reveals stories, patterns, clusters, relationships, and anomalies like outliers or missing data, that are not as obvious or are harder to see in table and text format.
In 2020, the COVID-19 pandemic has increased the volume and style of data visualisations that we see every day in the media. Further, in recent times statisticians and data scientists are acquiring and using increasingly complex and large datasets, including administrative and transactions data. These two factors have influenced our data visualisation work program.
Data visualisation is often separated into exploratory and explanatory visualisation. Explanatory work focusses on telling stories with data, conveying information to the audience in clear and appealing ways. In contrast, exploratory visualisation is about making sense of new data sources, understanding what’s going on in the data and determining how they could potentially be used in different ways. This assists analysts to assess the content of a new data source, see what’s interesting and plan more directed analysis. In some situations, there is overlap between these two types.
Examples of recent data visualisation work in the ABS include:
- exploratory visualisation of a range of new data sources
- designing new visualisations for Merchandise Trade data processing and some specialised reports
- establishing visualisation guidelines for different types of published materials
- exploring visual techniques for interpreting results from complex "black box" analysis methods and models so they’re easier to understand and explain (such as complicated machine learning methods)
- creating new types of dynamic graphs for social media. Some dynamic line plots were released in August-September 2020 showing how single touch payroll jobs have changed during the COVID-19 pandemic
Our upcoming work will include:
For more information, please contact Mary-Anne Stewart at email@example.com.
- exploratory visualisation of a range of new data sources and statistical methods - ABS is always investigating new sources and methods with the aim of reducing burden on survey respondents and providing richer information on the Australian economy and society
- exploring more visual techniques to support effective statistical processing - for example allowing quicker identification of anomalies and confirmation of clean data ready for release
- building ABS capability in different types of data visualisation
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