Progressive Data Analysis and Visualization
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 them 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. 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. The workshop will present state-of-the-art research and work-in-progress to design and implement PDAV systems.
Topics
This workshop will focus on progressive visualization and visual analytics. 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
Submission Guidelines and Format
Authors are invited to submit papers between two and four pages in length, excluding references, and using the standard IEEE conference paper template.
- https://tc.computer.org/vgtc/publications/conference/
- https://github.com/ieeevgtc/vgtc_conference_latex
To submit a paper, create an account and submit the paper to the submission system at: https://new.precisionconference.com/
Proceedings
PDAV will not have proceedings. Accepted papers will be published on the workshop website if the authors agree. Authors are free to publish their article as a preprint, e.g., arXiv.
Accepted papers will have an oral presentation at the workshop, and also a poster slot at the IEEE VIS poster session for additional exposure and interesting discussions
Important Dates
| Submission Deadline: (Extended) | 15th July 2024 | ||||
| Notification of Acceptance: | 31th July 2024 | ||||
| Camera Ready Paper and Poster: | 26th August 2024 | ||||
| All deadlines are at 23:59 (11:59 pm) AoE (UTC-12). |
Code of Conduct
Organizers
- Alex Ulmer, Fraunhofer IGD
- Jaemin Jo, Sungkyunkwan University
- Michael Sedlmair, University of Stuttgart
- Jean-Daniel Fekete, Inria & Université Paris-Saclay
Contact
For questions, please email the workshop chairs directly: pdav-chairs@ieeevis.org