Highlights From S-H-O-W Conference 2020
By: Mala Deep
Tags: Data Visualization, Graphic Design, Data, Conference, Data Journalism

COVID-19 has created us to bound us within the four walls, surfing the internet has been a window to explore the world. A few weeks ago, I studied a blog from Mollie Pettit at Nightingale, and I came to know about the S-H-O-W conference.

One of the most vital characteristics — or blessing, I must say — which distinguishes humans from other species on this planet is the process of learning. For Learning attending conferences, sharing a platform with great enthusiastic experts is worth the shot, so I started digging more into the conference’s landing page. I applied for the Diversity Scholarship. Luckily I got the opportunity to attend the conference.

S-H-O-W conference was organized by Graphic Hunters, a training institute on data visualization based in Utrecht, the Netherlands. This was the second S-H-O-W conference held on November 27& 28, 2020, through the online platform and for organizing the event: Anatomiegebouw, Bekkerstraat 141, Utrecht was used where we all examined, learned, and discussed the rules(make them and break them).

This article will go through a few highlights of several contents from this year’s conference (Due to the conference’s policy, I could not share the recorded links and related materials).

The list of Speakers @S-H-O-W Conference 2020. Note: Size & color is randomly picked. Image by the Author.

Manuel Lima

Principles are evocative and aspirational, whereas rules are rigid.

Manuel Lima is founder of VisualComplexity and a man with 15 years of experience designing digital experiences and is currently working on Google as design lead. He has been listed in the top 50 most creative and influential minds by the creative magazine.

His talk was based on data visualization principles with title COGNITIVE DESIGN: DECODING OUR BRAIN.

He states Principles as a fundamental quality or attributes determining the nature of something that is not step-by-step instruction. It is more evocative and aspirational, whereas rules are rigid. He strongly suggests exploring various design principles rather than binding them with rules.

He strongly suggest, always to try to be bounded within ethical responsibilities. He mentioned that data accuracy and integrity come first and should not distort or confuse the information for embellishment or partiality. Emphasis should be given to clarity and transparency, which is one of the main traits of data viz, and the designer should have.

We should also not keep preference to design choice over inherent facts and analytical finding and shared some of the dos and don’ts for viz.

Some of the takeaways are:

Be aware of zero baseline(start from zero value in the graph).

Look for the aspect ratio.

Data source attribution should be given.

Reduce cognitive load and time-to-understand.

Sandra Rendgen

The process of transforming abstract information into a graphic is by far more complicated.

Sandra Rendgen is an independent author, concept developer, and strategic consultant focusing on data visualization, interactive media, and the history of infographics. Her academic background is in art history and cultural theory.

Her talk was titled THE TREASURE HUNT — DEFINING THE RULES OF DATAVIZ.

The term “visualization” seems to suggest that all you need to do is pour numerical data into a visual template, and the increasing use of visualization tools supports this notion. But the process of transforming abstract information into a graphic is by far more complicated than that. Visualization does not just come about; it has to be developed in a long series of creative and editorial decisions.

She shared how the current design came into being. Shades for choropleth graphs in sequential data came from French mathematician Charle Dupin,1826. And walked us through other approaches regarding this. She strongly suggests that we look for some conventions like reading direction, color symbolism, chart types, etc.

She also sounded agreed with Manuel as she said that we should try to master all the basic principles, and then we can change rules based on context.

Lisa Charlotte Rost

Good design is hard to explain and even harder to create.

Lisa Charlotte Rost is a designer and blogger at Datawrapper: a web-based charting tool for journalists. She’s been writing and talking about data viz (and its rules) for a few years now and has created data visualizations for newsrooms like NPR, Bloomberg, SPIEGEL & ZEIT Online.

Her talk was titled WHAT TO CONSIDER WHEN CONSIDERING DATA VIS RULES.

By providing the analogy of BlackBox in between data/output to more output of Machine learning, she said that data would generate output/viz from rules. However, How many rules we have: Rules won’t be able to create a more creative design.

She significantly connected arts to data visualization. Formalism in the art which can be taken as style and innovation in data visualization.

Formalism: Style, Innovation.

Instrumentalism: Activism, Usefulness.

Expressionism: Expressing Emotion, Evoking Emotion.

Imitationaism: Showing Complexity, Truthfulness.

Institutionism: Awards, Endorsement.

However, one dataviz can amalgamate all these arts components.

She raised a good question for us.

What do you want your dataviz to be judged for?

Once we know our viz’s goal, then only rules can come before that. Focusing on the rule only is worthless.

Giovanni Magni

Every single rule could be shaped and adapted if this will make the project more effective.

Giovanni Magni is a designer. His work is focused on data-driven explorations and experiences. He is currently working as Head of data visualization at Accurate, a design studio based in Milano and New York City.

His talk was titled DATAGLITCHES — A HIGH-FIVE TO BROKEN CHARTS.

Giovanni succinctly gave the context to the glitches-images collected, explaining their role and evolution within the design process, which I found impressive.

Andy Kirk

It is hard to design for others effectively. It is harder if you don’t even care to try.

Andy Kirk is a UK-based data visualization specialist, consultant, trainer, author, and researcher. He founded the website VisualisingData, where a lot of resources and references can be found. Andy delivers workshops on information visualization and graphic literacy all around the world. In 2012 he wrote his first book on data visualization called Data Visualisation: a successful design process. In 2016 he released his second book called Data Visualisation: a Handbook for Data-Driven Design, which had a restyle in 2019.

His talk was titled DESIGN FOR YOUR AUDIENCE. OK, BUT HOW?

In this talk, Andy Kirk shared what it means to design for our audience. He pointed out the question from both the perceptive of the viewer and visualizer.

From Viewer:

What is useful for them to understand about this subject.

From Visualizer:

What is possible for me to show them about this subject.

And the union of these question’s answer is the relevance for designing the viz.

He explored the various aspects of classifying audience characteristics around motivation, capability, capacity, and pressure. Additionally, he looked at the different settings in which audiences may encounter or experience visualizations and how these affect design choices.

Some of the takeaways are:

Offer help-on-demand.

provided “How to read the graphs” section.

Scope for learnability.

Work can be

— — — — ->Explanatory: You show and tell.

— — — — ->Exhibitory: You show.

— — — — ->Exploratory: They explore.

So we can use a combination of these or use them in silos all based on our audience’s need.

Katie Peek

Please don’t underestimate your audience, But don’t overestimate them, either.

Katie Peek, Ph.D., is a journalist and data visualization designer who specializes in print graphics for science magazines. She is a contributing artist at Scientific American and regularly creates pieces for Audubon and the New York Times.

Her talk was titled THE DATA VIZ MULTIVERSE. Where she talked about how the audience can shape a graphic just as much as the source data can.

I loved the concept of adding a Nerd box: same info but in a different tone in data viz. She also shared one of the rules to be transparent about underlying data and its manipulation.

Some of the takeaways are:

Respect what the data can and cannot say.

Choose the example carefully and honestly.

Talk to experts.

Hannah Davis

Data Sonification: Representing data through sound and audio.

Hannah Davis is a generative musician and researcher based in NYC. She is the creator of TransProse, which programmatically translates text into a musical piece with a similar emotional tone. Her generated music has been played at The Louvre, the BMW Museum, the Fabrica Alta, and others. Currently, she is recording an album using generative techniques.

Her talk was titled DATA SONIFICATION. Where she talked about her data sonification experiments — from translating books into music based on their emotional content, creating musical stories from historical sound samples, and creating melodies from interesting datasets, to more recent experiments in generating music from the video.

She talked about the overlaps with generative music, machine learning, and subjective data, and talk about the invisible structures that can create meaningful output.

For me, data sonification was a new concept, and I was like, WOW.

Adrien Segal

The role of the artist is to ask questions, not answer them. — Anton Chekhov

Adrien Segal is an artist, drawing from landscape, science, history, emotion, and perception. Her sculpture synthesizes the information into knowledge as an intently human experience. Her work has been exhibited internationally since 2007 and is published in several books and academic journals. She has been awarded numerous Artist Residencies across the US, Canada, and Europe. Adrien was the Latham Fellow at IIT Institute of Design in Chicago in 2020 and has held Visiting Artist positions at Benchspace Cork in Ireland and at California College of the Arts, where she teaches art and design.

Her talk was titled DATA SCULPTURES. Where she talked about how physical patterns are being transformed into various objects like plywood, stone, etc. In a single word: Data Physicaization. She emphasis that by translating digital data into physical forms and materials, sensory perception, spatial cognition, and experience become how information is communicated into knowledge. Adrien also shared her data sculptures and her creative process and discussed how the human experience’s emotional nature drives how we seek to answer fundamental questions about life.

RJ Andrews

Column charts can also be called a pipe organ chart or Pipe-of-Pan chat.

RJ Andrews is an Award-winning data storyteller and founder of Info We Trust. He helps organizations solve information problems. Before concentrating on data visualization, RJ worked for NASA, the National Science Foundation, and Raytheon. He holds an MBA from the MIT Sloan School of Management and a Master of Science in Engineering from Northeastern University.

His talk was titled THE BAR CHART — OFFICIAL RULES & REGULATIONS. Where he talked about the history of bar charts and various forms used in the dataviz. He shared the emergence, evidence, examples, and exceptions to a different condition of bar chart rules along with considering the creative approaches lost and errors that somehow persist today. Most of all, we saw how important it is to be persistent in our vigilance toward designing charts that inform. We learned how to bar chart and unlock understanding of all charts and graphs.

Steve Haroz

Steve Haroz is a research scientist at Inria in Saclay, France. His research explores how the brain perceives and understands visually displayed information like charts and graphs.

His talk was titled PERCEIVING THE GIST — QUICK BUT BIASED. Where he talked about how the visual system makes quick judgments using lots of information. He also presented empirical research that shows limitations in our precision and neutrality when viewing visualizations.

Visualization creators often aim to “show the data” by presenting many raw individual items rather than only a simple summary statistic (such as an average). This approach allows viewers to see a “gist” or overview of the data, but it raises some important questions:

Are the rules the same when showing a few values vs. when showing many values?

When we make decisions, are we better off viewing lots of data or just a summary?

What properties of the data might bias our ability to perceive an accurate overview?

Some of the takeaways are:

The gist is prone to bias.

Gist and individual inspection are different.

Evanthia Dimara

Evanthia Dimara is a prospective Assistant Professor of Data Visualization at Utrecht University. Her fields of research are Human-Computer Interaction and Information Visualisation. She focuses on decision-making — how to help people make unbiased and informed decisions alone or in groups.

Her talk was titled as INTERACTION FOR DATA VISUALISATION — CAN WHAT YOU DO AFFECT WHAT YOU SEE?. Where she talked about the history of interaction in data visualization and discussed some of the below questions:

Can a static visualization be interactive?

Is there a way to compare the “interactivity” of different visualizations?

Which are the current interaction techniques in visualization?

How can we design novel interactions?

Shadi El Hajj

Adding an emotional and experiential dimension to our visualizations can turn data viz into an efficient communication vector.

Shadi El Hajj is a creative technology consultant operating at the intersection of software engineering, R&D, and digital art. He has worked for international clients over the last 15 years while creating digital dance performances, interactive installations, and algorithmic visuals at international festivals.

His talk was titled METAPHOR AND DATA VISUALS. Where he talked about metaphor and how it can impact the emotions and communication in data visualization.

Boris Muller

Great visualizations rely on the successful combination of science and design.

Boris is a professor for Interaction Design in Potsdam (Germany) and co-director of the Urban Complexity Lab — a research space at the intersection of design, science, and humanity. He has received a diploma in Graphic Design from the Hochschule für Künste Bremen (College of Art and Design Bremen, Germany) and a MA in Computer Related Design from the Royal College of Art London. His award-winning work focuses on generative design, data visualization, and science communication.

His talk was titled MAKING AND BREAKING RULES — VISUALISATION BETWEEN CREATIVITY AND USABILITY.

He highlighted two forms of rules:

Normative rules(prescriptive): Rigid and only one way to do it and should be made to.

Informative(descriptive) rules: Problem-oriented, bottom-up, looking how others are doing it.

He strongly suggests looking for goals, and based on the goal, we will have to work on visualization. He swiftly presents projects and methodologies which were ranging from generative design to speculative interfaces.