HEURISTIC EVALUATION: A GUIDE FOR USE IN INFORMATION VISUALIZATION - Information Visualisation: Techniques, Usability and Evaluation - page 180

Background and Overview
In the past, information visualization techniques were (in most cases)
presented without reporting evaluation results. Work focused primarily on
technical issues, what was possible to do, and less on actual potential
users' needs. In particular, the ability of users to deal with representations
and interactions, and making sense of them, received limited focus. In
2000, a special issue of the International Journal of Human-Computer
Studies [8] emphasized the need for a shift. Since then, usability (as
defined in the introduction [2][3]) and evaluation has been considered to
be highly important [9]. Today, user consideration and evaluation is
important to publication in information visualization. Evaluation is also a
research area where researchers are engaged in the challenge of refining
existing methods and metrics to suit contemporary information
visualization needs, and the development of innovations. One example is
the BELIV workshop series [10]. The workshop is a bi-annual meeting
(from 2012 onward, in which all fields of visualization are considered)
with the objective of:
…gathering researchers in all fields of visualization to continue the
exploration of novel evaluation methods, and to structure the knowledge
on evaluation in visualization around a schema, where researchers can
easily identify unsolved problems and research gaps.
Papers at the workshop are published in the ACM digital library. The
2012 workshop also resulted in a forthcoming special issue on evaluation
in the journal Information Visualization .
Evaluation offers a scientific approach to research and development in
information visualization. Results from evaluations provide a basis upon
which the next generation of developments can be built with greater
confidence and present evidence to encourage adoption by either industry
or the public [9][11]. A lack of evaluation studies, on the other hand, may
result in: (a) potentially useful visualization techniques not being accepted
and expanded upon, because there is no convincing evidence of usability,
measurable merits, and other useful information; and (b) less useful
visualization ideas being promoted (they may appear convincing through
pretty images and text, although they are not) [11].
There are a variety of definitions for evaluation, but a useful definition
of evaluation for studies in information visualization is “the systematic
acquisition and assessment of information to provide useful feedback
about some object” [12]. Thus, the general purpose of evaluation is to
process information and to receive “useful feedback.” More specifically,