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Topological Data Analysis Made Easy with the Topology ToolKit

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Academic paper
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Academic Paper attributes

arXiv ID
1806.081260
arXiv Classification
Computer science
Computer science
0
Publication URL
arxiv.org/pdf/1806.08126v10
Publisher
ArXiv
ArXiv
0
DOI
doi.org/10.48550/ar...06.081260
Paid/Free
Free0
Academic Discipline
Computer science
Computer science
0
Discrete mathematics
Discrete mathematics
0
Computer Vision
Computer Vision
0
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Computational geometry
0
Computer graphics
Computer graphics
0
Submission Date
June 21, 2018
0
Author Names
Julien Tierny0
Will Usher0
Qi Wu0
Julien Kitware0
Maxime Soler0
Attila Gyulassy0
Charles Gueunet0
Daisuke Sakurai0
...
Paper abstract

This tutorial presents topological methods for the analysis and visualization of scientific data from a users perspective, with the Topology ToolKit (TTK), a recently released open-source library for topological data analysis. Topological methods have gained considerably in popularity and maturity over the last twenty years and success stories of established methods have been documented in a wide range of applications (combustion, chemistry, astrophysics, material sciences, etc.) with both acquired and simulated data, in both post-hoc and in-situ contexts. While reference textbooks have been published on the topic, no tutorial at IEEE VIS has covered this area in recent years, and never at a software level and from a users point-of-view. This tutorial fills this gap by providing a beginners introduction to topological methods for practitioners, researchers, students, and lecturers. In particular, instead of focusing on theoretical aspects and algorithmic details, this tutorial focuses on how topological methods can be useful in practice for concrete data analysis tasks such as segmentation, feature extraction or tracking. The tutorial describes in detail how to achieve these tasks with TTK. First, after an introduction to topological methods and their application in data analysis, a brief overview of TTKs main entry point for end users, namely ParaView, will be presented. Second, an overview of TTKs main features will be given. A running example will be described in detail, showcasing how to access TTKs features via ParaView, Python, VTK/C++, and C++. Third, hands-on sessions will concretely show how to use TTK in ParaView for multiple, representative data analysis tasks. Fourth, the usage of TTK will be presented for developers, in particular by describing several examples of visualization and data analysis projects that were built on top of TTK. Finally, some feedback regarding the usage of TTK as a teaching platform for topological analysis will be given. Presenters of this tutorial include experts in topological methods, core authors of TTK as well as active users, coming from academia, labs, or industry. A large part of the tutorial will be dedicated to hands-on exercises and a rich material package (including TTK pre-installs in virtual machines, code, data, demos, video tutorials, etc.) will be provided to the participants. This tutorial mostly targets students, practitioners and researchers who are not experts in topological methods but who are interested in using them in their daily tasks. We also target researchers already familiar to topological methods and who are interested in using or contributing to TTK.

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