# Call for Contributions Topological Data Analysis has become, over the last few years, an established framework for the extraction and analysis of subtle 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 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 at being 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 a remodeling of the established TopoInVis workshop series, with the goal of being more diverse (in terms of applications) and inclusive (in terms of communities), with a clear will to open to other members of the visualization community potentially interested in topological methods, or experts in topological methods from other communities willing to experiment with interactive and visual applications. New in 2022: This year, in addition to full paper presentations, we will host a session of lightning talks (approx. 5 minutes) for early-career researchers (Ph.D. students, post-docs, etc.) to advertise their work to the community. Relevant topics include (but are not limited to): - Topological methods for the analysis and visualization of: * High dimensional point cloud data * Graph data * Scalar, vector, tensor, multi-field data * Time-varying data * Ensemble data * Uncertain data - Topological methods for data science (dimensionality reduction, clustering, etc.) - 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 We welcome contributions as regular papers in the IEEE VGTC format (up to 9 pages of content, plus up to 2 pages of references), as well as abstracts (at most 500 words) for early-career lightning talks. 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 and machine learning. Accepted papers will be published in the IEEE Xplore Digital Library. Important Dates: - June 21, 2022: abstract deadline for full papers - June 25, 2022: submission deadline for full papers - July 30, 2022: author notification - August 15, 2022: submission deadline for early-career lightning talk abstracts (500 words) - October 15-17, 2022: Workshop co-located with IEEE VIS Instructions for submission and further details will appear soon on the workshop website: <https://topoinvis.org/> https://topoinvis.org/ Program Chairs (alphabetic order): Talha Bin Masood (Linköping University, Sweden) Vijay Natarajan (IISc Bangalore, India) Paul Rosen (University of South Florida, USA) Julien Tierny (CNRS / Sorbonne University, France)