Kirk, Andy. Data visualisation: a handbook for data driven design. 2nd ed. London: SAGE Publications Ltd., 2019. , 312 p. ISBN 978-1-5264-6892-5. £34.99 (Paperback).
We missed reviewing the first edition of this book, which seems to on its way to becoming a classic in the area of data visualisation. The importance of converting data to some kind of image has long been recognized and there are some classic texts on the subject already, notably those by Edward Tufte (1983, 1990, 1997), which, it might reasonably be claimed, introduced many people to the ideas of data visualisation. Kirk's book is not the same kind of work as those by Tufte: it is, in effect, project based, a handbook for relating data appropriately to the purpose of a project. This is not surprising, since the author earns his living as a consultant to organizations, and as a trainer, rather than as an academic statistician (although he also teaches in universities). Readers who have been exposed to the nightly presentation of graphs in Covid-19 briefings, will, perhaps, be newly aware of the power of visualisations, as well as the limitations of the standard graphs that are used. Perhaps the author should have been retained, in the UK, by the Cabinet Office, to show them how to do it more effectively.
The book is divided into three parts: Foundations (Chapters 1 and 2); The hidden thinking (Chapters 3, 4 and 5); and Developing your design solution (Chapters 6 to 10). The first part defines the aim of data visualisation ('The visual representation and presentation of data to facilitate understanding' p. 15) and then goes on to elaborate a design process, involving four stages: formulating your brief, working with data, establishing your editorial thinking, and developing the design solution. This staged process clearly relates to the project-based approach adopted throughout the book.
The 'hidden thinking' of the second part of the book consists of all those things you need to do before you begin to think of visualising your data: what is your brief? That is, what purpose are the data going to serve in the context in which they are being used? Where is your data, how do you access it? And how do you think editorially about the data: what to include, what to leave out, what sequence of data presentations is required. These are, perhaps, the most important aspects of data visualisation, since once all the 'hidden thinking' is done, the rest of the process might almost take care of itself - almost, but not quite, since that is the scope of the third part of the book.
Given the purpose of the book, it is not surprising that the third part, 'Developing your design solution', should occupy more than half of the total pages. It begins with a typology of the marks and their attributes used in visualisation (e.g., a line and its length), and then presents a catalogue of chart types in five categories: categorical—comparing categories and distributions of quantitative values; hierarchical—revealing part-to-whole relationships and hierarchies; relational—exploiting correlations and connections; temporal—plotting trends and intervals over time; and spatial—mapping spacial patterns through overlays and distortions (p. 138). This is a very useful catalogue and might stimulate some to create better PowerPoint slides.
The last four chapters deal with important aspects of design: building in degrees of interactivity so that, for example, a user of the product can filter the information presented; using annotation to explain the functions of the visualisation; the effective use of colour; and composition, the most important elements of which are layout, arrangement and sizing. The book ends with a short Epilogue on the development cycle, and there is a useful bibliography and index. There is also a very useful Website associated with the book, which presents additional content, examples of good practice, guides to tools and other resources, and a monthly guide to the "Best of..." all of these.
We know that this is a text of proven value, simply by the fact that it is the second edition and that this and the first edition have been reprinted several times. Anyone interested in, or needing to know about data visualisation, need look no further. There is one oddity, given that this is a design-oriented book: why did the book designer choose to print bulleted points in grey, rather than black? Instead of pointing up their importance in the text this actually manages to minimise it, since if something is "greyed out" it is generally of less significance. It is also harder to read. Perhaps the author can reflect on this in the next edition.
- Tufte, E.R. (1983). The visual display of quantitative information. Graphics Press,
- Tufte, E.R. (1990). Envisioning information. Graphics Press.
- Tufte, E.R. (1997). Visual explanations: images and quantities, evidence and narrative. Graphics Press
Professor T.D. Wilson
How to cite this review
Wilson, T.D. (2020). Review of: Kirk, Andy. Data visualisation: a handbook for data driven design. 2nd ed. London: SAGE publications ltd., 2019. Information Research, 25(2), review no. R689 http://www.informationr.net/ir/reviews/revs689.html
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