Process and Pitfalls in Writing Information Visualization Research Papers - Information Visualization: Human-Centered Issues and Perspectives - page 141

the technique is suitable for the problem. Most do not close the loop with a
validation that the proposed solution is effective for the target users.
In contrast, a strong design study would be rather dicult for an outsider
unfamiliar with the infovis literature to write. Two critical aspects require a
thorough understanding of the strengths and weaknesses of many visualization
techniques. First, although a guideline like “clearly state the problem” might
seem straightforward at first glance, the job of abstracting from a problem in
some target domain to design requirements that can be addressed through visu-
alization techniques requires knowing those techniques. Second, justifying why
the chosen techniques are more appropriate than other techniques again requires
knowledge of the array of possible techniques.
The flip side of this situation is that design studies where visualization re-
searchers do not have close contact with the target users are usually also weak. A
good methodology is collaboration between visualization researchers and target
users with driving problems [18](Chapter 3.4).
All That Coding Means I Deserve a Systems Paper: Many significant
coding efforts do not lead to a systems paper. Consider whether or not you have
specific architectural lessons to offer to the research community that you learned
as a result of building your library or toolkit.
Neither Fish nor Fowl: Papers that try to straddle multiple categories often
fail to succeed in any of them. Be ruthlessly clear about identifying your most
important contribution as primary, and explicitly categorize any other contribu-
tions as secondary. Then make structural and validation choices based on the
category of the single primary contribution.
3 Middle Pitfalls: Visual Encoding
If you have chosen the design route, then a major concern in the middle stages
of a project should be whether your visual encoding choices are appropriate and
justifiable.
Unjustified Visual Encoding: An infovis design study paper must carefully
justify why the visual encoding chosen is appropriate for the problem at hand.
In the case of technique papers, where the focus is on accelerating or improving a
previously proposed technique, the argument can be extremely terse and use a ci-
tation to a previous paper. But in the case of a design study, or a paper proposing
a completely new technique, your justification needs to be explicit and convincing.
One of the most central challenges in information visualization is designing the
visual encoding and interaction mechanisms to show and manipulate a dataset.
A straightforward visual encoding of the exact input data is often not su-
cient. In many successful infovis approaches, the input data undergoes significant
transformations into some derived model that is ultimately shown. Many weak
papers completely skip the step of task analysis. Without any discussion of the