Step-by-step advice on how to create simple, impactful data visualisation specifically using qualitative data. It can be used as an upgrade to your QDA training or as a standalone data visualisation textbook.
Learn to meet your day-to-day needs in creating data visualisation, without needing a qualification in graphic design or computational science.
The 8-step guide aids you in creating simple data visualisations that clearly communicates your qualitative data.
The author:
• Draws on real-world data to inform your own representations of data
• Provides easy to replicate examples to help you learn by doing
• Compares case studies from around the world
• Features advice from experts across the social sciences, and related industries.
Whether you are taking a course, or just one lecture, this is the ideal companion to help you transform your data visualisation.
Part 1: The power of visualizations
Chapter 1: Introduction
Chapter 2: The power of visualizations and graphics in qualitative data
Part 2: An eight-step method for visualizing qualitative data
Chapter 3: Preparing the data to be visualised (Steps 1-3)
Chapter 4: Composing your data visually (Steps 4-6)
Chapter 5: Getting and implementing feedback (Steps 7-8)
Part 3: Practical aspects for producing and disseminating your
visualizations
Chapter 6: Thinking about space, balance, colour and arranging elements
correctly
Chapter 7: Collaborating with a visual artist
Chapter 8: Sharing your visualization
Part 4: A visual summary of the book
Chapter 9: A visual summary of the book
Dr. Maria Loroño-Leturiondo is a postdoctoral researcher at the Basque Centre for Climate Change, Spain. She received her doctoral degree from Manchester Metropolitan University, masters degree from the University of Copenhagen, and bachelor degree from the University of the Basque Country. She has taught qualitative and quantitative courses on social research methods. Her research interests include adaptation to climate change as well as science communication. She has produced design work for different scientific outputs including books, conferences, journals, and events.
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