Call for Contributions
Topological methods have become an established framework for the extraction and analysis of structural patterns in complex data. It has been successfully applied in a variety of application fields, including quantum chemistry, astrophysics, fluid dynamics, combustion, material sciences, biology, and data science. In particular, the genericity, efficiency, and robustness of topological methods have made them particularly well suited for the multi-scale, interactive analysis and visualization of the underlying structural information of data.
Despite their rising mainstream popularity, topological methods still face a number of challenges, including, for instance, efficient computational methods for large-scale time-varying data, the characterization of noise and uncertainty, or the support of emerging data types, such as ensemble data or high-dimensional point clouds.
The IEEE VIS Workshop on Topological Data Analysis and Visualization aims to be an inclusive forum for the fast dissemination of the latest results in theory, algorithms, and applications of topological methods for the interactive and visual analysis of data. This workshop is open to members of the visualization community interested in topological methods and to experts in topological methods from other communities willing to experiment with interactive and visual applications.
The workshop welcomes submissions of both full-length papers and posters. The accepted papers will be presented during the workshop, and the accepted posters will be presented at the main poster event at VIS and give a lightning talk during the workshop.
Scope
Relevant topics include (but are not limited to):
- Topological methods for the analysis and visualization of all types of data, including but not limited to:
Graph data
- Scalar, vector, tensor, multi-field data
- Time-series data
- High dimensional point cloud data
- Ensemble data
- Data with uncertainty
- Topological methods for data science (dimensionality reduction, clustering, etc.)
- Topological methods and machine learning
- Computational methods for topological data analysis and visualization
- Software systems for topological data analysis and visualization
- Visual analytic frameworks relying on topological methods
- Applications of topological data analysis and visualization
Submission
We welcome contributions as regular papers in the IEEE VGTC format (up to 9 pages of content, plus up to 2 pages of references). Paper submissions will be peer-reviewed by an international program committee, including experts in topological methods for scientific data, information visualization, visual analytics, computational geometry, computational topology, and machine learning. Accepted papers will be published in the IEEE Xplore Digital Library.
Poster contributions should adhere to the IEEE VIS Guidelines. While VIS has no specific formatting requirements, posters can be no larger than size A0 (841 x 1189 mm / 33.1 x 46.8 inches) and must be in a portrait orientation. The accepted posters will be presented at the main poster event at VIS.
Important Dates
- June 14, 2024: abstract deadline for full papers
June 21, 2024June 28, 2024: submission deadline for full papers- July 31, 2024: author notification
August 7, 2024August 31, 2024: submission deadline for posters- October 14, 2024, afternoon: Workshop at IEEE VIS
All deadlines are in Anywhere on Earth (AoE) time zone.