[Infovis] Submission Deadline June 15: Call for Papers: Interactive Visual Analytics and Visualization for Decision Making - Proceedings in IEEE Digital Library

[David S. Ebert]

We are soliciting papers in interactive visualization and analytics for
decision making and scientific discovery as part of the Interactive Visual
Analytics and Visualization for Decision Making: Making Sense of Big Data
minitrack  of the Decision Analytics Track at HICSS 50. Accepted paper will
appear in the proceedings as well as the IEEE Digital Library. HICSS is
always one of the top conferences for downloads in the IEEE Digital Library!

 

A description of the paper topics is below, the minitrack RFP is below, and
the conference RFP is available at http://www.hicss.org/#!authors/ccjp.
Please contact us with any questions.

 

We look forward to receiving your submissions by June 15,

 

David, Brian, Kelly

 

 

David Ebert

Brian Fisher

Kelly Gaither

 

 

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Dr. David S. Ebert,  Silicon Valley Professor of ECE, Purdue University


Director, Visual Analytics for Command, Control, and Interoperability
Environments  

   http://www.VisualAnalytics-CCI.org <http://www.visualanalytics-cci.org/>


Director, Purdue Visualization and Analytics Center, www.purvac.org
<http://www.purvac.org/>    

ebertd at purdue.edu http://www.ece.purdue.edu/~ebertd


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CFP:

 

Interactive Visual Analytics and Visualization for Decision Making 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. Current applications include environmental
science and technologies, natural resources and energy, health and related
life sciences, precision medicine, safety and security and business
processes. Submissions are encouraged that extend the areas of use to new
analytic tasks in science and technology, public health, business
intelligence, financial analysis, social sciences, and other domains.
Particular emphasis will be given to submissions that use visual analytics
for social change discovery, analysis and communication. 

 

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. 

 

We are also seeking submissions on 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: 

.         Visualization and Analysis of datasets of varying size and
complexity from archives and real-time streams

.         Collaborative visual analysis and operational coordination within
and across organizations.

.         Interactive and Visual Risk-based decision making

.         Interactive Machine Learning methods

.         Cross-platform interoperability, from mobiles to data walls

.         Managing response time of complex analytical tasks

.         Effective deployment and case studies of success from deployed
visualization and analytics experiences

.         Social media and streaming data visual analytics

.         Visualization and analytics for data-driven policy making and
decision support

.         Business intelligence, organizational, financial, and economic
decision making visual analytics

.         Issues and Challenges of evaluation of visual decision making 

.         Cognitive and social science aspects of visual decision-making
environments

For HICSS 2018, we encourage authors to address these themes from their own
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.  

 

Both algorithmic "data sciences" approaches and human-centered
"visualization" and "visual analytics" human-computer interface methods hold
great promise for operationalizing massive datasets and streaming data in
support of a broad range of human activities. Applications in basic
scientific research, business analytics, health sciences, environmental
science and engineering R&D explore the implications of these methods for
advancement of knowledge and strategic planning. Applications in
coordination, command, and control of complex human activities such as crowd
and traffic management, disaster relief, law enforcement, and national and
cyber security add the constraints of real-time performance and distribution
of planning to the challenges faced. 

 

For this mintrack we invite computational, cognitive, and organizational
perspectives on advanced data processing and interactive visualization
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. 

 

 

 

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Dr. David S. Ebert,  Silicon Valley Professor of ECE, Purdue University


Director, Visual Analytics for Command, Control, and Interoperability
Environments  

    <http://www.visualanalytics-cci.org/> http://www.VisualAnalytics-CCI.org


Director, Purdue Visualization and Analytics Center,
<http://www.purvac.org/> www.purvac.org   

 <mailto:ebertd at purdue.edu> ebertd at purdue.edu
<http://www.ece.purdue.edu/~ebertd> http://www.ece.purdue.edu/~ebertd


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