2019 Visual Communication Symposium @ Rice University—Ambassador's Report

We do a terrible job of translating the insight we gain from conferences into value for our departments. We attend, we participate, we get a great deal of stimulating information for ourselves—but we don’t share with those in the offices next door.

Thus, this report, which distills the 2019 Rice Visual Communication Symposium (VCS) for the rest of Lamar University’s Department of Communication and Media. You may find it completely useless to you. More likely, you’ll find it interesting and, hopefully, at least a little useful. Or, ideally, you’ll find something inspiring here that you’d like to explore in your own teaching or research. Keep in mind that data visualization isn’t something I’m super deep into—at least not yet.

Before I dive in, can we please just take a moment to appreciate how beautiful Rice University is? This was my first visit.

Book recommendations

Here are two books that sounded interesting and relevant to share:

Key Takeaways for Different Specialties


There are huge opportunities for our students in data visualization and data exploration. Goodman’s talk on Glue convinced me we should be looking for ways to teach our students to dig deep into data sets, while Jacobs’s and Kurgan’s presentations had great examples of journalistic storytelling. Jacobs’s was the better documented, so if you’re looking for examples of great interactive digital storytelling, along with detailed guides on replicating his successes, take a peek at his work below.

Public Speaking

Early sessions were very focused on communicating information at a glance by boiling down information to its essentials. In particular, see Cheng’s talk on visual abstracts, the lessons from which can be applied to any situation in which you need to communicate complex information quickly (such as in a PowerPoint slide).


Data visualization and exploration can be used to enrich anyone’s research, whether in the conceptualization, analysis, or presentation stage. Remember, I don’t consider myself a quantitatively oriented researcher, but I am convinced the tools and concepts discussed in the conference can make my research stronger. That doesn’t necessarily mean adding a little quant to your qual—but it could, and I think it will in my case. For others, it may be simply conveying your ideas more clearly and quickly through occasional illustration. It doesn’t matter if your illustrations look a little amateurish! It’s about communicating effectively, and that doesn’t require an art degree.

Session-by-Session Highlights

Bang Wong, Broad Institute, bang@broadinstitute.org

Wong’s talk, the first of the symposium, focused on some best practices and basics in data visualization. It was a good crash course but is now difficult to summarize. I won’t try. Instead, I’ll direct your attention to the book recommendations from the conference, through which you can enter into the topic.

Karen Cheng, University of Washington, kcheng@uw.edu

Cheng focused on helping scientists create stronger visual abstracts, which are graphical representations of the major findings of academic articles. I wish we had something like visual abstracts in my own field, and I think I’m going to start offering them when I can to accompany journal submissions. Among Cheng’s most important and generalizable ideas:

  • Shaker philosophy should be at the core of everything visual we create. It’s core idea is: “Don’t make anything unless it’s both necessary and useful. But if it is both necessary and useful, don’t hesitate to make it beautiful.”

  • Design is not decoration

  • Communicating visually don’t require being artistic. To paraphrase Cheng, no one says “you’re just not a writer, so give up communicating through writing.” But we do say “you’re just not a creative/artistic person” to kids starting in middle school. Anyone can illustrate, especially for themselves and within their field.

  • Her study found that the following five steps to improving visual abstracts let people to assume the article they previewed would be better written, to assume the author was smarter, and to better understand what the article would be about. Other research shows aesthetically pleasing work is thought to be more credible. Her steps are as follows:

  1. Visually structure your graphic. For example, if you’re representing a process, steps should move left to right.

  2. Emphasize key information. Choose one idea to represent the work, even though the article may consist of multiple major ideas.

    • This is key. She gave the example of Steve Jobs talking to an advertiser. Jobs wanted to make an ad showing all the features of an eMac. The advertiser threw five pieces of paper at Jobs, who failed to catch them all. Then he threw Jobs one, which he caught easily. Get it?

  3. Make graphics as simple as possible. Eliminate anything that is nonessential, and chunk info into groups (chunking as we do in phone numbers (409-554-3858 rather than 4-0-9-5-5-4-3-8-5-8)).

  4. Choose colors to label and show relationships

  5. Tell a story

All of this functions similarly to a news lead: It sparks interest, but it also provides immediate value, as intrigue isn’t enough.

  • One last insight from Cheng dealt with collaborating with others. As she explained it, each person has a “T” of knowledge that benefits from being paired with another’s T. Here’s the way I sketched out the idea:

Scan 10 copy.jpg

Alyssa Goodman, Harvard University, agoodman@cfa.harvard.edu

Goodman’s presentations were brilliant, but they are the hardest for us to benefit from. She’s developed a tool called Glue, which allows you to explore data by linking attributes across multiple datasets and interacting with them simultaneously. Glue’s completely free, but the time required to learn and implement it would be substantial unless you’re already deep into data analysis.

A few other things she shared:

  • Guidelines for planning and creating better data visualizations, with examples and explanations, can be found here.

  • You can write articles w/ embedded, interactive data visualizations made on Glue and other applications using Authorea and other services.

  • WorldWideTelescope is an incredible tool for exploring space. Its “tours” are examples of two-way storytelling that allows readers to shift between exploration and explanation. Additionally, she mentioned WWT can be used as a GIS.

Brian Jacobs, National Geographic, brian.jacobs@natgeo.com

Jacob is graphic editor for National Geographic. He worked on the interactive story “Losing Ground” about climate change in Louisiana with Pro Publica. His goal was highlighting his interactive journalism through three examples: a story on bird migration patterns, another about a dinosaur, and a third about Cassini’s plunge into Saturn. I have some notes on the processes he used to make those stories, and he wrote write papers about the processes that he said are on his website. He also shared a link to his slides.

My main takeaways was that he considers legibility to be the benchmark of success (rather than, say, page views). I also came up with an assignment idea for an advanced multiplatform journalism course in which students could take an already published story and represent it in the way he did his work, which would be a semester-long project.

Laura Kurgan, Columbia University

Kurgan’s presentation included some very interesting pseudojournalistic storytelling art projects. One of the most important ideas she raised relevant to our work was an interesting way of visualizing the lives of social media posts, in her case, of censored content on Weibo. I’m sure it could be found online, although she didn’t share how.

Farès el-Dahdah, Rice University (humanities!)

A historian! El-Dahdah has made incredible maps that link in, overlay, and make interactive photos and civic plans throughout time that can be manipulated from year-to-year. Check them out:

He mentioned that he’s experimenting with technology that georeferences the latitude, longitude, and altitude of points on a photograph by correlating them in each pixel of an image with known GIS points. It’s called moloplotting, and he’s working on it w/ some Swiss company called WSL.

His projects are diplomatic. For his Houston project, for example, he tries to partner with anyone who could possibly be interested in his success, such as the department on campus concerned with civil planning and the city itself.

But he’s also cunning. He secured the support of IT for his Rio project by creating the Rice project, which he called a “Trojan Horse.” The university was naturally excited to provide the infrastructure for that project (which was largely built on the skeleton of his Rio one). He was then able to push his Rio content in through the same door.

Kirsten Siebach, Rice University

She’s one of the 400 scientists who control the Curiosity rover on Mars. She shared some incredible photos taken by Curiosity and provided insight into how rover projects work. It wasn’t particularly useful information for me, but it was fascinating.

Ideas for myself

I had two flashes after el-Dahdah’s presentation, which was probably the most inspirational for me:

  • I could scrape data from historical Denver city directories and correlate it with photographs and stuff. This is mostly a way to build greater storytelling tools for narrating historical events.

  • I could visualize historical news/information infrastructure and use those maps to explore how that infrastructure varies over time and is utilized by communities in crisis.

Ken Ward