For those who have been eagerly awaiting resources that we used in our session, here they are, along with a few bonuses!
From our activities:
To learn about how storyboarding can help you visualize data as a team, check out the this summary from Amanda Makulec (JSI). Participants in the session talked about how the process helped to underscore the importance of defining your audience up front in order to drive what you pick as your key messages, and that the exercise was a great way to collaborate with a team to create a common vision for a visualization product.
For more on simple data viz best practices, check out this Building Your Viz Checklist from Erica Nybro (DHS Program) that can help you evaluate your visualization. It’s amazing how much you can improve a graph or chart with a few simple tweaks like decluttering by deleting excess lines and tick marks or using color strategically.
Bonus! And in case you’re interested in more resources, check out our Love Your Data and Free Viz Tools handouts from earlier presentations. For a more detailed deep dive on viz, check out the Data+Design eBook.
Many thanks to the attendees at today’s Mini U session, “A Data Viz Makover: Approaches for Improving Data Visualization.” We’ve got two great round ups of data viz resources for you, featuring work by colleagues and thought leaders who we admire and think you’ll love, and a forthcoming post with our resources and handouts from the session. Let’s use great visualizations to make sure data doesn’t get wasted!
From some of our favorite thought leaders:
- Information is Beautiful – Great examples and ideas
- Storytelling with Data | Cole Naussbaumer – Cole features both examples and practical templates that you can use when designing visualizations in Excel. Also consider checking out her in-person training events, which have gotten rave reviews!
- Intentional Visualization | Stephanie Evergreen – One of the US thought leaders in data visualization, Evergreen was one of the founders of the American Evaluation Association Data Visualization & Reporting Technical Interest Group and continues to be a leading voice in the data viz space.
- Ann Emery’s Excel Tutorials – Some of the best simple videos for improving your visualizations in Excel. Ann’s other resources on her site are also excellent, and she’s available for external presentations and workshops.
- Policy Viz | Jon Schwabish – Full of helpful hints, Excel hacks, and data viz makeovers. Jon is also an excellent trainer on presentation design and visualizations; you can find more details on his website.
- The Functional Art | Alberto Cairo – A leading professor on information design who has authored text books and hosted MOOCs on infographic design.
Great summary resources in data viz tools and approaches for design include:
- Data Visualization Resource Guide – A round up of available tools for designing visualizations, as well as some great framing on why visualizing information is essential for promoting information use.
- Data+Design eBook – One of the most comprehensive (free) guides to visualization design, coauthored by nearly 100 contributors from across the domain. Includes considerations for visualization before even undertaking your data collection processes and great step-by-step instructions on data cleaning, analysis for visualization, chart design, and more.
And for some great data viz humor and tips, check out Fresh Spectrum | Chris Lysy (to whom all credit for the awesome cartoon illustrations of this post should go).
I often argue that a chart’s y axis should always start with zero. Cole Nussbaumer (storytellingwithdata.com) and Jon Schwabish (policyviz.com) recently had a conversation about this very topic and posted it at storytellingwithdata.com, along with some example charts. In summary, Cole and Jon agreed that column/bar charts should always start their y-axis with zero. Because our eyes focus on the height of that bar, a non-zero axis distorts the relationship between columns. Savvy viewers of the chart may also be more skeptical about the truth of our visualization when they notice that the axis doesn’t start at zero.
But what if you really need to focus on small but meaningful differences between data points? Line graphs might be ok here depending on the context, because the focus in a line graph is on the relative position of the points in space rather than the height of the bars. But the relative positions can still be overstated by a non-zero axis.
One solution Cole and Jon (and I!) like is to present 2 charts side-by-side: one that has a zero-starting y axis to show the context of the data, and another that does not start at zero, but instead zooms into the chart to show the variation within a smaller range.
Listen to the whole conversation at storytellingwithdata.com. Are there any examples in global health/development where a non-zero axis works?