When I tell the story of how we designed a visualization or a whole Web application for a particular service in EMBL-EBI [1:R5], these methods stand center stage. Although the importance of qualitative fieldwork and analysis has been highlighted, for example, in the design study methodology framework of Sedlmair et al. [6], my impression is that these popular UX methods are still not routinely embedded in the everyday process of data visualization researchers and practitioners.

The emphasis on what people see in the cover story reinforced this impression.

At EMBL-EBI we bring together
experts from industry and academia
to address current challenges in data
visualization faced by our industry
partners [1:R6] in an attempt to bridge
the gap between data visualization
researchers, the HCI community, UX
practitioners, and domain experts
(especially from the pharmaceutical
Iread the cover story of the July– August 2018 issue of Interactions on data visualizations by Danielle Albers Szafir with great interest, particularly since I recently gave an introductory webinar on this topic for the European
Bioinformatics Institute (EMBL-EBI)

(see [1:R1]).

The article focuses on “understanding what people see when they look at a visualization” to design visualizations “that support more accurate data analysis and avoid unnecessary biases.” This is valuable, particularly within the context of a how-to article that needs to be brief and practically applicable.

However, I think the cover story
would have been even stronger if it:
• cited some additional seminal
background work in relation to what
people see; and
• mentioned, even in passing, the
importance of studying what people do,
which has been fairly firmly established
within the UX and HCI communities.

In particular, I think it would have been useful to mention the ranking of visual channels ([ 2, 3] and [1:R2]) especially given that position is considered an even better way to encode quantitative data than sequential or divergent color maps. In the recent review by O’Donoghue et al.

[1:R3], Figure 2 provides an excellent visual overview of the ranking combined with succinct practical advice on the use of color maps.

Additionally, given that the
article is about graphical integrity, I
was expecting it to refer to Edward
Tufte [ 4], to whom this principle
is attributed. Mentioning Tamara
Munzner’s textbook [ 5] would have
been useful too for those who are
new to the field but want to study
interactive visualizations in more
depth.

My own audience is early-career life scientists, so I based my webinar on the Points of View columns on data visualization in Nature Methods [1:R4], which is a familiar and inspirational journal for them. Given that some of the examples in the cover story came from biology, citing this resource may also have been helpful for that readership.

In my role as a UX practitioner, I rely on particular methods such as interviews and contextual observations to understand the needs of life scientists, to capture these needs (typically as user personas and task models), and to formulate the question that we are trying to answer with a visualization (e.g., as a problem statement or a job to be done). In other words, I focus as much on what people do as on what people see by applying methods that are fairly established within the HCI and UX communities.

What People See Versus What People Do

Some Thoughts on the Cover Story on Visualizations
@INTERACTIONSMAG 6 INTERACTIONS JANUARY–FEBRUARY2019
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Nikiforos Karamanis,

European Bioinformatics Insititute (EMBL-EBI)

The Interactions website ( interactions.acm.org) hosts a stable of bloggers who share insights and observations on HCI, often challenging current practices. Each issue we’ll publish selected posts from some of the leading and emerging voices in the field.