Data visualisation (also data visualization or dataviz) is an umbrella term for converting data sources into a visual representation and can include charts, spreadsheets, graphs, maps, tables, animations, and data art. In short, it is the process used to create data graphics.
Data visualisation can be used to analyse and better understand your research dataset as well as communicate your dataset and research story to an audience. According to Yau (2013), a good visualisation should enable you to see "trends, patterns, and outliers that tell you about yourself and what surrounds you" (p. xi).
Yau, N. (2013). Data points: Visualization that means something. John Wiley & Sons.
With so many data visualisation tools to choose from, these curated collections can direct you to the best resources for your needs.
Visual elements such as graphs, charts and diagrams can be used to craft a narrative and present information in an accessible and understandable way.
Timelines visually represent elements in chronological order. If you have data with a time stamp, this may be a useful visualisation to consider.
For more mapping tools and applications see the Geographic information system (GIS) and mapping section of this guide.
Network visualisation involves the visualisation of connections and relationships in your data.
There are many tutorials and resources available to help you use data visualisation tools.
RMIT staff and students have access to numerous resources on data visualisation. Some of the resources below can help get you started.
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