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</head><body style="color: rgb(0, 0, 0);" text="#000000">Dear
colleagues--- Please consider
submitting a paper to the Interactive Visual Analytics for Knowledge
Integration and Decision Intelligence ( Decision Analytics and Service
Science Track, HICSS 56) by <span style="display: inline; font-size:
inherit; padding: 0px;" class="__postbox-detected-content
__postbox-detected-date"
__postbox-detected-content="__postbox-detected-date">June 15, 2022</span>
to be held at the Hyatt
Regency Hotel, Maui <span style="display: inline; font-size: inherit;
padding: 0px;" class="__postbox-detected-content
__postbox-detected-date"
__postbox-detected-content="__postbox-detected-date">January</span> <span
style="display: inline; font-size: inherit; padding: 0px;"
class="__postbox-detected-content __postbox-detected-date"
__postbox-detected-content="__postbox-detected-date">3-6, 2023.</span> <br>
<br>
Interactive Visual Analytics for Knowledge Integration and Decision
Intelligence supports human decision making through interaction with
data and statistical and machine learning processes, with applications
in a broad range of situations where human expertise must be brought to
bear on problems characterized by massive datasets and data that are
uncertain in fact, relevance, location in space and position in time. In
partnership with organizations in defence, health care, and business,
visual analytics research methods combining laboratory studies,
cognitive ethnography, and field experiments have aided the design of
information systems for decision making about injuries to children,
multiomic precision health, radiological diagnosis, and VR for conflict
zone operations. <br>
<br>
Submissions are encouraged that focus on the core issues of theory and
methods for visualization, analytics, knowledge integration and decision
intelligence in organizations. Case studies of applications of these
methods to new analytic and decision making tasks in science and
technology, public health, business intelligence, financial analysis,
social sciences, and other domains are particularly welcome. Submissions
may include studies of visual analytics and decision support in the
context of an organization (e.g., communication between analysts and
policy-makers), perceptual and cognitive aspects of the analytic task,
Interactive Machine Learning, and collaborative analysis using visual
information systems. Additionally, submissions may include
understandable, trustable AI as well as human-guided AI to round out the
problem-solving process. Emphasis will be given to submissions that use
visual analytics for social change discovery, analysis, communication,
and focus on mixed-initiative human/AI analysis.<br>
<br>
This proposal builds upon our successful HICSS-47, HICSS-48, HICSS-49,
HICSS-50, HICSS-51, HICSS-52, HICSS-53 and HICSS-54 +HICSS-55 minitracks
on visual analytics for decision support and our earlier minitracks on
visual analytics, mobile computing, and digital media at scale. It seeks
to define analytical methods and technologies that use interactive
visualization to meet challenges posed by data, platforms, and
applications for decision making and risk-based decision making:<br>
<br>
Analysis of multi-perspective knowledge integration, synthesis and
engineering in organizations.<br>
Use of interactive visualization and visual analytics in digital
economies<br>
Visual analytics and visualization in “wicked” problem solving in
organizations<br>
Analysis of datasets of varying size and complexity from archives and
real-time streams<br>
Collaborative visual analysis and operational coordination within and
across organizations.<br>
Interactive and visual risk-based decision making<br>
Interactive machine learning methods<br>
Managing response time of complex analytical tasks<br>
Effective deployment and case studies of success from deployed
visualization and analytics experiences<br>
Visualization and analytics for data-driven policy making and decision
support<br>
Issues and challenges in evaluation of visual decision making<br>
Mixed-initiative analysis methods for decision making<br>
Cognitive and social science aspects of visual decision-making
environments<br>
<br>
For HICSS 2023 we extend our focus to multidisciplinary collaboration
among researcher from a variety of research perspectives. Authors are
encouraged to bring the lens of their own background and expertise to
focus on the analytics of the data itself and coordination of multiple
levels of analysis, decision-making and operations to the design and
evaluation of effective presentations for stakeholders. We invite
computational, cognitive, and organizational perspectives on advanced
data processing and interactive visualization for analysis and
decision-making across a range of human endeavors. We also invite
participation from researchers who are looking at scaling issues and
multiscale issues, whether these scales refer to the time of decision
making, the form-factor and operational constraints of mobile devices,
the number of decision makers or the more traditional notion of
multiscale simulation and real-world scales of data. We are particularly
interested in approaches that combine computational and interactive
analytics in “mixed initiative” or Interactive Machine Learning systems,
decision support in the context of an organization (e.g. communication
between analysts and policy-makers), perceptual and cognitive aspects of
the analytic task, and collaborative analysis using visual information
systems. <br>
<br>
More information about this minitrack can be found here:
<a class="moz-txt-link-freetext"
href="https://hicss.hawaii.edu/tracks-56/decision-analytics-and-service-science/#interactive-visual-analytics-for-knowledge-integration-and-decision-intelligence-minitrack"
style="color: rgb(0, 157, 247);">https://hicss.hawaii.edu/tracks-56/decision-analytics-and-service-science/#interactive-visual-analytics-for-knowledge-integration-and-decision-intelligence-minitrack</a>
. Please see author instructions at: <a class="moz-txt-link-freetext"
href="https://hicss.hawaii.edu/authors/" style="color: rgb(0, 157,
247);">https://hicss.hawaii.edu/authors/</a>
and feel free to contact the co-chairs with any questions.<br>
<br>
Minitrack Co-Chairs:<br>
David Ebert <br>
Purdue University<br>
<a class="moz-txt-link-abbreviated" href="mailto:ebertd@purdue.edu"
style="color: rgb(0, 157, 247);">ebertd@purdue.edu</a><br>
<br>
Brian Fisher<br>
Simon Fraser University<br>
<a class="moz-txt-link-abbreviated" href="mailto:bfisher@sfu.ca"
style="color: rgb(0, 157, 247);">bfisher@sfu.ca</a><br>
<br>
Kelly Gaither<br>
University of Texas at Austin<br>
<a class="moz-txt-link-abbreviated" href="mailto:kelly@tacc.utexas.edu"
style="color: rgb(0, 157, 247);">kelly@tacc.utexas.edu</a><br>
<br>
--
<br>
<div class="moz-signature">-- <br>
<div><span style="color: #a6192e;"><b>Brian D.
Fisher, Ph.D.</b></span><br>Professor <span style="color: #993300;">|</span> School
of Interactive Arts and Technology<br><br><span style="font-size:
10pt;">Faculty of
Communication, Art and Technology <span style="color: #993300;">|</span>
Simon Fraser University</span><br><span style="font-size: 10pt;">Rm.
7475 <span style="color: #993300;">|</span> 13450-102 Avenue, Surrey BC,
V3T 0A3</span><br><span style="font-size: 10pt;">T: +1 (778) 873 -7324 </span><br>
<span style="font-size: 10pt;"><br>
<br>
<span style="color: #993300;"></span></span></div>
<div><img src="http://www.sfu.ca/%7Eapillay/SFU_HORIZ_SIG.png"><br><br><span
style="font-size: 9pt;">At
Simon Fraser University, we live and work on the unceded
traditional territories of the Coast Salish peoples of the
xʷməθkwəy̓əm (Musqueam), Skwxwú7mesh (Squamish), and
Səl̓ílwətaɬ (Tsleil-Waututh) Nations.</span></div>
</div>
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