The submission deadline is extended to the 15th of July. Take the chance to submit your late-breaking research results, or give your planned submission the final touch! https://ieee-vis-pdav.github.io/ We solicit contributions that focus on progressive visualization and visual analytics The increasing amount of data is a long-standing challenge for data analysis systems. Although building interactive systems has been a central focus of the visualization community, when applied to large-scale data and complex algorithms, most current visualization systems suffer from long, unmanaged computation delays between user interactions and system responses, rendering the systems unusable. The critical challenge we face here is to make a system’s latency manageable, ultimately ensuring it remains below the golden limits of human latency regardless of the amount of input data and complexity of algorithms. Progressive Data Analysis and Visualization (PDAV) is a novel programming paradigm to control latency by replacing long computations with a series of smaller computations with bounded latency, improving iteratively until the whole computation is completed or until the user is satisfied with the latest iteration and stops. Thus, PDAV computations also need to inform the user about the quality of the result to allow early decisions with controlled quality. With PDAV, visual exploration systems can scale to large data sizes and use complex algorithms interactively, provided they are adapted to run progressively. This new paradigm is promising but will require important research and technical work to become mainstream. This workshop is aimed at explaining and accelerating the development of the paradigm. The workshop will present state-of-the-art research and work-in-progress to design and implement PDAV systems. We encourage late-breaking work, research in progress, and position papers; for example, topics of interest to the workshop include (but are not limited to): Progressive Techniques for Information and Scientific Visualization Progressive Visual Analytics Systems Progressive Algorithms and Data Structures Progressive Databases and Data Management Systems Progressive Machine Learning Progressive Artificial Intelligence Progressive Data Science User Interfaces for Progressive Systems Languages and Toolkits for Progressive Systems Uncertainty in Progressive Systems Infrastructure for Progressive Systems Human Factors in Progressive Data Analysis Applications of Progressive Visual Data Analysis Theories for Progressive Visual Data Analysis Evaluation of Progressive Systems Important Dates Submission Deadline: 1st July 2024 Notification of Acceptance: 19th July 2024 Camera Ready Paper and Poster: 26th August 2024 Workshop (1/2 Day, Morning): 14th October 2024 Organizers Alex Ulmer, Fraunhofer IGD Jaemin Jo, Sungkyunkwan University Michael Sedlmair, University of Stuttgart Jean-Daniel Fekete, Inria & Université Paris-Saclay More info: https://ieee-vis-pdav.github.io/ For questions, please email the workshop chairs directly: pdav-chairs@ieeevis.org Alex, Jaemin, Michael & Jean-Daniel -- Jean-Daniel Fekete Jean-Daniel.Fekete@inria.fr Aviz Team Leader Inria, Université Paris-Saclay INRIA Saclay Centre www.aviz.fr/~fekete Bat 660, Université Paris-Saclay tel: +33 1 69156551 F91405 ORSAY Cedex, France fax: +33 1 69154240