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 ---------------------------------------------------------------------------- -------------------------------- 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@purdue.edu> ebertd@purdue.edu <http://www.ece.purdue.edu/~ebertd> http://www.ece.purdue.edu/~ebertd ---------------------------------------------------------------------------- -------------------------------- 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.