PUMA publications for /user/hermann/series%20tracking;https://puma.ub.uni-stuttgart.de/user/hermann/series%20tracking;PUMA RSS feed for /user/hermann/series%20tracking;2024-03-29T08:34:31+01:00VA(2): A Visual Analytics Approach for // Evaluating Visual Analytics
Applicationshttps://puma.ub.uni-stuttgart.de/bibtex/2cc131f8c378577ab621d7a274ca4c61d/hermannhermann2017-05-18T11:32:12+02:00aloud; analytics; data} evaluation; eye interaction logs; qualitative series thinking time tracking; {visual <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tanja Blascheck" itemprop="url" href="/person/15effcc98e8efb3870ffb9ba9a527edfb/author/0"><span itemprop="name">T. Blascheck</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Markus John" itemprop="url" href="/person/15effcc98e8efb3870ffb9ba9a527edfb/author/1"><span itemprop="name">M. John</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kuno Kurzhals" itemprop="url" href="/person/15effcc98e8efb3870ffb9ba9a527edfb/author/2"><span itemprop="name">K. Kurzhals</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Koch" itemprop="url" href="/person/15effcc98e8efb3870ffb9ba9a527edfb/author/3"><span itemprop="name">S. Koch</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Thomas Ertl" itemprop="url" href="/person/15effcc98e8efb3870ffb9ba9a527edfb/author/4"><span itemprop="name">T. Ertl</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">22 </span></span>(<span itemprop="issueNumber">1</span>):
<span itemprop="pagination">61-70</span></em> </span>(<em><span>January 2016<meta content="January 2016" itemprop="datePublished"/></span></em>)<em>10th IEEE Conference on Visual Analytics Science and Technology (VAST) /
IEEE VIS Conference, Chicago, IL, OCT 25-30, 2015.</em></span>Thu May 18 11:32:12 CEST 2017{10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA}{IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}{JAN}{10th IEEE Conference on Visual Analytics Science and Technology (VAST) /
IEEE VIS Conference, Chicago, IL, OCT 25-30, 2015}{1}{61-70}{VA(2): A Visual Analytics Approach for // Evaluating Visual Analytics
Applications}{Article; Proceedings Paper}{22}{2016}aloud; analytics; data} evaluation; eye interaction logs; qualitative series thinking time tracking; {visual {Evaluation has become a fundamental part of visualization research and
researchers have employed many approaches from the field of
human-computer interaction like measures of task performance, thinking
aloud protocols, and analysis of interaction logs. Recently, eye
tracking has also become popular to analyze visual strategies of users
in this context. This has added another modality and more data, which
requires special visualization techniques to analyze this data. However,
only few approaches exist that aim at an integrated analysis of multiple
concurrent evaluation procedures. The variety, complexity, and sheer
amount of such coupled multi-source data streams require a visual
analytics approach. Our approach provides a highly interactive
visualization environment to display and analyze thinking aloud,
interaction, and eye movement data in close relation. Automatic pattern
finding algorithms allow an efficient exploratory search and support the
reasoning process to derive common eye-interaction-thinking patterns
between participants. In addition, our tool equips researchers with
mechanisms for searching and verifying expected usage patterns. We apply
our approach to a user study involving a visual analytics application
and we discuss insights gained from this joint analysis. We anticipate
our approach to be applicable to other combinations of evaluation
techniques and a broad class of visualization applications.}