All guides: Digital tools for research: Data visualisation

Introduction to data visualisation

Data visualisation / data visualization (dataviz) is an umbrella term for converting data sources into a visual representation (can include charts, spreadsheets graphs, maps, tables, animations, 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

Good data visualisation illuminates patterns and tells a research story. According to Yau*, the best data visualisation, "evokes that moment of bliss when seeing something for the first time, knowing that what you see has been right in front of you, just slightly hidden...and enables you to see trends, patterns, and outliers that tell you about yourself and what surrounds you".

Yau, N. (2013). Data points visualization that means something (1st edition). John Wiley & Sons, Inc., p. xi

Melbourne Urban Forest data visualisation

Melbourne Urban Forest Visual
The City of Melbourne maintains more than 70,000 trees. This data viz website created by RMIT School of Design senior lecturer Greg More enables you to explore this dataset and some of the challenges facing Melbourne’s Urban Forest.

Data visualisation tools and applications

Curated collections of dataviz tools

My Favorite Tools: Alberto Cairo on Data Visualization
Albert Cairo is the director of visualization, data communication and information design at University of Miami. These are his recommendations for tools to improve visual data and to make graphics more accessible.
Selected Tools Data Visualization
Tools the people behind Datavisualization.ch work with and recommend.
UFS Data visualisation tools
Collection of data visualisation tools curated UFS Library.

Graphs, charts, diagrams

Excel, SPSS, Storyline, InfraNodus, Tableau Public, D3, Python, R

* Note: RMIT provides licences to some commercial software packages (e.g. SPSS) for staff and students. Please visit the ITS lists of software available to staff and students to see what software you are eligible to access and how to obtain access.

Tableau Public Gallery
Data visualisation examples from across the web created with Tableau Public.
Plotly
Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.
RAWGraphs
RAW Graphs is an open source data visualisation framework that links data spreadsheets to clear visualisations.

Timelines

Timeline, Timeglider, Tiki-Toki Timeline Maker

TimelineJS
TimelineJS is an open-source tool that enables anyone to build visually rich, interactive timelines. Experts can use JSON to create custom installations

Maps

Tableau Public, D3, QGIS, mapbox, ArcGIS StoryMaps

QGIS
QGIS is an open-source geographic information system that allows you to create, edit, visualise, analyse, and publish geospatial information.

Networks

Gephi, Tableau Public, Cytoscape, NodeXL, D3, Neo4j

ImagePlot
Open source software tool that visualises collections of images and video of any size. ImagePlot's visualisations shows the actual images in your collection.
Gephi
Gephi is open-source visualisation and exploration software for graphs and networks, allowing users to interact with the representation, manipulate the structures, shapes and colours to reveal hidden patterns.

Resources and training

Tutorials and Resources

Flowing Data Tutorials
Tutorials for presentation, analysis and understanding created by data visualisation blogger Nathan Yau (Flowing Data).
The Fuctional Art Tutorials
Online tutorial world-renowned visualization professor Alberto Cairo shares with his students during the first few weeks of classes in his Visual Journalism and Interactive Media programs at the University of Miami (includes: Flourish, iNZight, RAWgraphs, Data Illustrator, QGIS)
Data Visualisation Catalogue
Project developed by Severino Ribecca to create a library of different information visualisation types.
Tips for visualizing COVID-19 data
Rowan Philp from the International Journalist's Network argues that data visualisation tools have emerged one of the most powerful vehicles for public understanding of COVID-19. Lists 10 tips for how to get the visualisation of COVID-19 data right
Cookbook for R
Includes a useful section on creating graphs with R.
Data Visualization Society Resources
Annotated and regularly updated resources prepared by the US based Data Visualization Society.

Library resources and LinkedIn Learning

Click to link to resources (e-books, videos etc) available in Library Search on data visualisation

Data Visualization: A Lesson and Listen Series (LinkedIn Learning) by Shander, Bill
"Learn about key themes in data visualization, data storytelling, and information design, and listen to interviews with leading designers and data visualization experts. Follow along with expert Bill Shander in this series exploring key themes in data visualization, data storytelling, and information design."
Data Visualization: Best Practices (LinkedIn Learning)
"Build data visualizations that are accurate and compelling. Learn to create charts and graphs that look great and stand up to analysis. This course focuses on best practices, not tools to walk you through the ins and outs of creating accurate and compelling data visualizations."
Data Visualization in Society by Kennedy ENGEBRETSEN
ISBN: 9463722904
Publication Date: 2020-04-16
Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.

Library subject guides

Digital tools for research