Information Visualization Blogs
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eagereyes — Robert Kosara’s influential blog. Kosara is Senior Research Scientist at Tableau Research and previously Associate Professor of Computer Science at UNC Charlotte.
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flowingdata — Nathan Yau, a former statistics PhD from UCLA, has maintained a data vis blog and online training materials for some time.
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chartable — A blog written by people at Datawrapper, a visualization tool aimed at those publishing online content.
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data stories — Podcast series led by Enrico Bertini and Moritz Stefaner.
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adventures in viz — Rob Radburn’s blog, featuring numerous excellent visual data analyses using Tableau, often with a geographic flavour.
Conferences
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IEEE VIS — The conference at which leading Data Visualization work is published through a special issue of Transactions on Visualization & Computer Graphics.
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OpenVis Conf — New, exciting conference. Presenters are academics and practitioners work at the leading-edge of data visualization. Videos of talks from previous conferences are published online. From the 2018 conference, I’d recommend Matt Kay’s on Uncertainty Visualization, Maarten Lambrechts' Xenographics and Heather Krause’s F-Word.
Readings
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Heer, J., Bostock M. & Ogievetsky, V. (2010) A tour through the visualization zoo. An excellent introduction to the DNA of data graphics — the mappings between visual characteristics and properties of data that define particular 'species' of visualization. Changing these mappings results in different graphic types : bar chart, scatter plot, pie chart, etc..
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Jones, B. (2014) Communicating Data with Tableau, O’Reilly. I don’t actually know this book, but colleagues have recommended it. Certainly worth considering if you are to continue working with Tableau.
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Meirelles, I. (2013) Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations. Contains excellent examples and advice on designing graphics. The explanations of principles developed from knowledge of perception and cognition are especially good.
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Meyer, M. & Fisher, D. (2018) Making Data Visual, O’Reilly. I’ve only read a sample chapter, but it’s written by highly respected InfoVis profs and has a great ambition: If you’re a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way.
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Munzner, T. (2014) Visualization Analysis & Design, CRC Press. Tamara Munzner, Professor of Information Visualization at University of British Columbia, provides a systematic and empirically-grounded framework for thinking about visualization. Available as an e-book via the University of Leeds Library. Chapters 2 and 5 are worth special consideration.
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Tufte, E. (2001), The Visual Display of Quantitative Information, Graphics Press, Cheshire, Connecticut. Often seen as the go-to explanation and demonstration of graphical excellence. It’s a collection of the good (and bad) in graphics with explanations of key principles that can help you achieve the former and avoid the latter. Definitely worth reading Tufte’s thoughts on chart junk, data-ink ratio, the lie-factor and also some of his re-designs.
Content by Roger Beecham | 2018 | Licensed under Creative Commons BY 4.0.