#SWDchallenge: recommended reading
When I started using graphs early in my career and became interested in the field of data visualization and using graphs to communicate, there were only a handful of books on this topic. Fast-forward two decades, and there are many (including my own!).
This is fantastic—whether visualizing data is embedded in our job, or something pursued as an interest/hobby, we all get to be part of a growing field of knowledge. But it can also be hard to keep up, or to know which historical books remain relevant.
This month, my aim is to use our collective knowledge to build a robust data visualization, data storytelling, visual design, and presentation bookshelf and collect potentially varied opinions and perspectives on the titles. In addition to recommending a non-previously-shared title (more on that in the challenge instructions below), you can contribute productively this month by adding your review(s) to recommendations that have already been made by others, or comment or ask questions about the title. Also be sure to add datapoints to books you have read and enjoyed.
I invite you to use this to share your already-established love of a particular book, critique a contemporary or classic, or read something you’ve been meaning to and share it along with your thoughts (both praise and thoughtful criticism are welcome). Diverse and unconventional titles will enrich the collection, so feel free to think outside the box. As always, a broad interpretation is welcome, including books that may not be directly about the above subject matter areas, but where there are applicable learnings or relevance that you’d like to highlight.
Let’s work together to build an amazing shared resource of knowledge this month!
The challenge
Share your review of a data visualization, data storytelling, or otherwise relevant-to-this-community book.
IMPORTANT: As a first step, browse submissions made so far this month [add link] and select a title to review that has not already been shared. This will help us keep all the recommendations and opinions related to a particular book in one spot, as well as encourage greater variety in our libraries.
Please title your submission with the book title and use an image of the book cover for your primary image (feel free to share additional images to supplement if you’d like).
If someone has already submitted a review for the book you had chosen, we encourage you to add your thoughts to the given submission as a comment. If maintaining a challenge streak is a consideration, however, you will also need to submit your own not-previously-shared book to do so. You can also share feedback on others’ reviews or ask questions you may have about the given title and add datapoints to those books you’ve read and enjoyed.
As part of your submission, I encourage you to let us know both why you chose the particular book and in what scenarios and for what reader/audience you recommend it. If you have any personal anecdotes or experiences related to how the book has influenced your work, please include those as well.
Struggling to decide what to include in your review? Consider the following:
Overview/purpose: What is the primary focus of the book, and what audience is it written for (e.g. beginner vs. expert, specific industry, tool-related knowledge)?
Key takeaways: What are one or two key takeaways or memorable insights you gained from this book?
Impact on your perspective: How has reading this book influenced or changed your perspective on data visualization and storytelling?
Practical applications: How does the book address the practical application of its concepts? Are there examples, case studies, or exercises that help in applying these ideas?
Visual design & quality: How well does the book utilize visual design elements? Are the graphics, charts, and layouts effectively used to enhance understanding?
Strengths & weaknesses: What are the book’s greatest strengths? Are there areas where it falls short or aspects that could be improved?
Relevance & timeliness: How relevant is the book’s content to current practices in data visualization and storytelling? Does it address modern challenges and technologies?
Accessibility & readability: How accessible is the writing style? Is the content approachable for its intended audience?
Recommendation: Would you recommend this book to others? If so, to whom, and why?
Share your review(s) in the SWD community by February 29th at 5PM ET.
I’ll close by reminding those reading that no one sets out to write a bad or otherwise ineffective book, so while I absolutely encourage you to be honest in the review(s) you share, please also be kind. When providing criticism, please do so in a constructive manner.
