- Make sure that the individual graphics that make up your infographic have been “flattened.” That means that all design elements and layers have been rolled up into one graphic file (JPG, GIF, PNG, etc.). If the graphics are not flat, the tagging process can cause elements to drop off or become corrupted.
- Once the graphic areas are “flat,” use Adobe Acrobat Pro to add your tags. Mark each area of text as text and, for graphic images, add as much information as you can into the alt text. You should include the title of each graphic elements, describe what it shows or any trend it demonstrates.
- Once all areas have been tagged, make sure that the reading order is correct so that the different areas of the infographic will be read in an order that makes sense.
- Add metadata to the properties.
The recently released “Women’s Lives and Challenges” report from The DHS Program features 3 infographics summarizing the major findings in women’s empowerment, experience with violence, and control. Each infographic focuses on women in a different part of the world. All the visuals in the report are available on Pinterest.
Designing these infographics was a challenging process. We needed to represent women from 3 regions (Latin America, Africa, and Asia), we needed to capture a lot of indicators over time, and we were dealing with very sensitive subject matter, such as domestic violence.
This project really proved that designing infographics takes a team: the researchers who know the data and always want to accurately represent the numbers; the communicators who know how to pull a simpler story out of hundreds of tables; and designers who find creative ways to illustrate complex themes.
Development of these infographics also reminded us that data visualization for development poses some unique hurdles: fantastic graphic designers in the U.S. may not have a feel for what homes in Africa look like, or what women in the developing world go shopping for; their visualization would not ring true in many DHS countries.
After several rounds of adjustments, the DHS team is pleased with the outcome. What do you think? How would you visualize these data?
We often talk about data visualization as beginning with the data, identifying the audience and then culling the most interesting, compelling story from that data that leads the receiver of said data to act. The FiveThirtyEight Blog about data journalism really resonated with me. It’s a long post, complete with interesting visuals, but if you read to the end you’ll find the photo of Nate’s bookshelf and the questions he poses about the trade-off between making it look pretty and making it useful and efficient. Here he raises one of the major challenges that we face in the age of big data and visual overload – in a nutshell…
how to make data [journalism] vivid and accessible… without sacrificing rigor and accuracy.
Take a look and see what you think.
Thanks to Logan Harper, from MPH@GW for this submission on their experiences developing mini-infographics:
To raise awareness for MPH@GW’s Walk Away from Diabetes 2013 campaign, we created a series of mini-infographics featuring startling facts about Type II diabetes. We chose the format of mini-infographics to encourage sharing and promotion on social media during American Diabetes Month. The 400×400 pixel size (recommended for Facebook, but also works for Instagram, Twitter, and Pinterest) so we could only feature one fact or idea per image.
We were really pleased with the reception across social media networks and recommend the use of mini-infographics for similar campaigns.
Thanks to new Hub member Dr. Doug Storey for sharing this upcoming conference that aims to explore the interaction between comics and the discourse of healthcare. This year’s conference aims to highlight the relationship between comics, personal health narratives and public health issues such as barriers to healthcare and the stigma of illness… Can comics be considered Data Viz? Let us know if you’re going and what you think!
Thanks to new Hub member Jeff Knezovich of the Institute of Development Studies at the University of Sussex for sharing some work he’s been doing on Data Viz. Check out the Data Visualization Competition for Think Tanks in Developing Countries – they’ve pulled together a great list of Data Viz Resources , including tools, blogs and open data sets.
Have no fear: if your tool of choice is the ubiquitous Microsoft Excel, you can still create beautiful visualizations (though we’ll show you great examples of other platforms on the Hub).
Ann Emery has excellent short video tutorials in her for creating interesting graphs using Excel and some creative maneuvering of data, rows, and columns.
Think about how to make your Excel graph or chart sing with simple visual tools: change fonts, color palettes, and use other formatting tricks to trick people into thinking you used a fancy viz tool. Make it simple and easy by changing your color palette to a custom one, maybe looking to some of the color selection tools around the web for inspiration.
Think about your choice of chart types: avoid creating pie charts, which can be hard for the human eye to see, and consider horizontal bar charts instead of vertical ones, which give you more space for your axis labels and categories. Simple is wonderful when it comes to creating visualizations that communicate well.
Finally, and perhaps most importantly, recognize that just because Excel can create a certain graph or chart type from your data, that doesn’t mean it’s a great fit. Think about choosing the right chart type to tell your data story, and beware the funhouse effect on your data (distorting meaning) caused by the poorly designed three-dimensional graphs that Excel creates with the click of a button.
Have any great examples of your own #ExcelHacks? Or some fun Excel fails that we can all learn from? Share them on the Hub, or simply link to your work in the comments below!