[Infovis] CFP: Interactive Visual Analytics and Visualization for Decision Making - Making Sense of a Growing Digital World Minitrack ( Decision Analytics and Service Science Track, HICSS 55)

[Ebert, David]

    Dear colleagues--- Please consider submitting a paper to the Interactive Visual Analytics and Visualization for Decision Making - Making Sense of a Growing Digital World Minitrack ( Decision Analytics and Service Science Track, HICSS 55) by June 15, 2021. Please see author instructions at: https://hicss.hawaii.edu/authors/ and feel free to contact the co-chairs with any questions.



    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 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.

    Visual analytics and visualization in digital economies

    Visual analytics and visualization in “wicked” problems

    Visualization in organizational analytics

    Visual analytics/visualization for trustable, explainable AI

     Visual analytics for Human-guided, interactive AI

    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

    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

    Cognitive and social science aspects of visual decision-making environments



We also welcome  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.

    Minitrack Co-Chairs:

    David Ebert

     University of Oklahoma

     ebert at ou.edu<mailto:ebert at ou.edu>

    Brian Fisher

     Simon Fraser University

     bfisher at sfu.ca<mailto:bfisher at sfu.ca>

    Kelly Gaither

     University of Texas at Austin

     kelly at tacc.utexas.edu<mailto:kelly at tacc.utexas.edu>



Dr. David S. Ebert,  Gallogly Chair Professor of ECE and CS
Associate Vice President of Research and Partnerships
Director, Data Institute for Societal Challenges (DISC)
University of Oklahoma
5 Partners Place
201 Stephenson Pkwy, Ste 4600
Norman, OK 73019
ebert at ou.edu<mailto:ebert at ou.edu>