Papers due June 15, 2024
Conference is January 7-10, 2025
Hilton Waikoloa Village, Big island
https://hicss.hawaii.edu/
The demands of decision-making in an increasingly interconnected world mandates that complex real-time data analytics will combine with organizational knowledge integration, synthesis, and engineering to a key role in decision-making. 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.
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.
This minitrack 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:
• Analysis of multi-perspective knowledge integration, synthesis and engineering in organizations.
• Use of interactive visualization and visual analytics in digital economies
• Visual analytics and visualization in "wicked" problem solving in organizations
• 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
• Managing response time of complex analytical tasks
• Effective deployment and case studies of success from deployed visualization and analytics experiences
• Visualization and analytics for data-driven policy making and decision support
• Issues and challenges in evaluation of visual decision making
• Mixed-initiative analysis methods for decision making
• Cognitive and social science aspects of visual decision-making environments
• Visual decision-making in the context of Trustable AI or mis/disinformation
• Theory-enhanced automated detection of fake news and fake comments (with visualization)
For HICSS-58, we extend our focus to multidisciplinary collaboration and communication 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, communication, and operations to the design and evaluation of effective presentations for stakeholders and dissemination of trustful and actionable information. We invite computational, cognitive, communication, 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, including developing trustable AI and the challenge of dis/misinformation.
Minitrack Co-Chairs:
David Ebert (Primary Contact)
University of Oklahoma
ebert@ou.edu
Brian Fisher
Simon Fraser University
bfisher@sfu.ca
Kelly Gaither
University of Texas at Austin
kelly@tacc.utexas.edu
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Brian Fisher
Full Professor
Simon Fraser University
Surrey BC
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