[Infovis] [CFP] First IEEE VIS Workshop on Progressive Data Analysis and Visualization (PDAV)

[Jean-Daniel Fekete]

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 at ieeevis.org

Alex, Jaemin, Michael & Jean-Daniel
-- 
  Jean-Daniel Fekete       Jean-Daniel.Fekete at 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