We are soliciting papers in interactive visualization and analytics for decision support, operational management, and scientific discovery as part of the Interactive Visual Decision Analytics 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 - Dr. David S. Ebert, School of Electrical and Computer Engineering - - Silicon Valley Professor of Electrical and Computer Engineering - - Purdue University; 465 Northwestern Ave., West Lafayette, IN 47907 - - Director, Visual Analytics for Command, Control, and Interoperability - - Environments (VACCINE), DHS CCI Center of Excellence - - http://www.VisualAnalytics-CCI.org - - Director, Purdue Visualization and Analytics Center, www.purvac.org - - ebertd@purdue.edu http://www.ece.purdue.edu/~ebertd - ---------------------------------------------------------------------------- ------------ Minitrack: Interactive Visual Decision Analytics DECISION ANALYTICS, MOBILE SERVICES AND SERVICE SCIENCE Interactive Visual Decision Analytics supports human decision making through interaction with data and statistical and machine learning processes. IVDA applies in 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. We also encourage submissions that extend the areas of use to new analytic tasks in science and technology, public health, business intelligence, financial analysis, and other domains. 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. 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, and collaborative analysis using visual information systems. We seek 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, such as: . 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 . 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 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" 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. 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 and operations to the design and evaluation of effective presentations for stakeholders ---------------------------------------------------------------------------- -------------------------------- 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 Vice President Publications and 1st VP, IEEE Computer Society Director, Purdue Visualization and Analytics Center, <http://www.purvac.org> www.purvac.org <mailto:ebertd@purdue.edu> ebertd@purdue.edu <http://www.ece.purdue.edu/~ebertd> http://www.ece.purdue.edu/~ebertd ---------------------------------------------------------------------------- --------------------------------