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 Know your audience: Why data communication needs to pay attention to
novice users 
 Data visualizations researchers have no clear idea of what makes someone
a novice 

  Date:
      July 5, 2023
  Source:
      University of Massachusetts Amherst
  Summary:
      Computer scientists recently found that data-visualization experts
      have no agreed-upon understanding of who makes up one of their
      largest audiences -- novice users. The work is an important first
      step in ensuring more inclusive data visualizations, and thus data
      visualization that works for all users.


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FULL STORY
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Computer scientists at the University of Massachusetts Amherst recently
found that data-visualization experts have no agreed-upon understanding
of who makes up one of their largest audiences -- novice users. The work,
which recently won a coveted Best Paper Award at the Association for
Computing Machinery's conference on Human Factors in Computing Systems
(ACM CHI), is an important first step in ensuring more inclusive data
visualizations, and thus data visualization that works for all users.

Data visualization is the representation of data in a visual and
easily understandable way using common graphics such as charts, plots,
infographics and animations. Using visual elements provides an accessible
way to see and understand trends, outliers and patterns in data. One of
the most familiar data visualizations -- the pie chart -- is legible to
nearly everyone and has been a method used to quickly convey information
since its invention in the early nineteenth century.

But, with the advent of the internet, the range, reach and complexity of
such visualizations have grown exponentially. Think of the various online
COVID trackers, graphics showing economic projections or the outcomes
of national elections. "More and more, everyday people are relying on
data visualizations to make decisions about their lives," says Narges
Mayhar, assistant professor in the Manning College of Information and
Computer Science at UMass Amherst, and the paper's senior author. "Even
many of our collective decisions rest on data visualizations."  Since a
visualization's use is dependent on its intelligibility, one would
think that data visualization experts would have a clear and standard
understanding of their audience, particularly their non-expert users. And
yet, "despite many decades of data-visualization research, we had no clear
notion of what makes someone a 'novice,'" says Mayhar. This insight was
important enough that the ACM CHI, the premier international conference
for human-computer interaction, bestowed the Best Paper Award on the
research, an honor reserved for the top 1% of submitted papers.

Mayhar, lead author Alyxander Burns, who completed the research as
part of his graduate studies at UMass Amherst, and their co-authors
combed through the past 30 years of visualization research and found 79
papers spread across seven academic journals that concerned themselves
with identifying the audience for data visualizations. Within those 79
papers, they found that the definitions of a novice user ranged widely,
from people who have difficulty "effectively utilizing GPU clusters"
to those who lack knowledge of "ontological models."  Moreover, the team
found that most researchers' sample groups of users overwhelmingly skewed
toward white, college-aged people living in the U.S.

"How do we know that the visualizations we create could work for older
people, for those without college degrees, for people living in one of
the world's many other countries?" asks Mayhar. "We need to be clear,
as a field, what we mean when we say 'novice,' and the goal of this paper
is to change the way that visualization researchers think about novices,
address their needs and design tools that work for everyone."
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==========================================================================
Journal Reference:
   1. Alyxander Burns, Christiana Lee, Ria Chawla, Evan Peck, Narges
   Mahyar.

      Who Do We Mean When We Talk About Visualization Novices? Association
      for Computing Machinery's conference on Human Factors in Computing
      Systems (ACM CHI), 2023 DOI: 10.1145/3544548.3581524
==========================================================================

Link to news story:
https://www.sciencedaily.com/releases/2023/07/230705142920.htm

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