© 2017

Topological Methods in Data Analysis and Visualization IV

Theory, Algorithms, and Applications

  • Hamish Carr
  • Christoph Garth
  • Tino Weinkauf
Conference proceedings TopoInVis 2015

Part of the Mathematics and Visualization book series (MATHVISUAL)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Topology-Based Analysis of Multi-Variate Data Sets

    1. Front Matter
      Pages 1-1
    2. Alexander Kuhn, Wito Engelke, Markus Flatken, Hans-Christian Hege, Ingrid Hotz
      Pages 35-50
    3. Lars Huettenberger, Christian Heine, Christoph Garth
      Pages 51-65
  3. Topological Techniques for High-Dimensional Data

    1. Front Matter
      Pages 67-67
    2. Sebastian Volke, Dirk Zeckzer, Martin Middendorf, Gerik Scheuermann
      Pages 69-85
    3. Patrick Oesterling, Christian Heine, Gunther H. Weber, Dmitriy Morozov, Gerik Scheuermann
      Pages 87-101
  4. Scalar Field Topology

    1. Front Matter
      Pages 119-119
    2. Himangshu Saikia, Hans-Peter Seidel, Tino Weinkauf
      Pages 121-134
    3. Attila Gyulassy, Aaron Knoll, Kah Chun Lau, Bei Wang, Peer-Timo Bremer, Michael E. Papka et al.
      Pages 135-149
    4. Léo Allemand-Giorgis, Georges-Pierre Bonneau, Stefanie Hahmann
      Pages 151-168
  5. Vector and Tensor Field Topology

    1. Front Matter
      Pages 169-169
    2. Ronald Peikert, Gustavo Machado, Filip Sadlo
      Pages 171-186
    3. Lei Zhang, Robert S. Laramee, David Thompson, Adrian Sescu, Guoning Chen
      Pages 187-203
    4. Wieland Reich, Mario Hlawitschka, Gerik Scheuermann
      Pages 205-219
    5. Yue Zhang, Yu-Jong Tzeng, Eugene Zhang
      Pages 221-234
  6. Coherent Structures

    1. Front Matter
      Pages 235-235
    2. Mingcheng Chen, John C. Hart, Shawn C. Shadden
      Pages 237-251

About these proceedings


This book presents contributions on topics ranging from novel applications of topological analysis for particular problems, through studies of the effectiveness of modern topological methods, algorithmic improvements on existing methods, and parallel computation of topological structures, all the way to mathematical topologies not previously applied to data analysis.

Topological methods are broadly recognized as valuable tools for analyzing the ever-increasing flood of data generated by simulation or acquisition. This is particularly the case in scientific visualization, where the data sets have long since surpassed the ability of the human mind to absorb every single byte of data.

The biannual TopoInVis workshop has supported researchers in this area for a decade, and continues to serve as a vital forum for the presentation and discussion of novel results in applications in the area, creating a platform to disseminate knowledge about such implementations throughout and beyond the community.

The present volume, resulting from the 2015 TopoInVis workshop held in Annweiler, Germany, will appeal to researchers in the fields of scientific visualization and mathematics, domain scientists with an interest in advanced visualization methods, and developers of visualization software systems.


data analysis topology geometry visualization coherent structures

Editors and affiliations

  • Hamish Carr
    • 1
  • Christoph Garth
    • 2
  • Tino Weinkauf
    • 3
  1. 1.University of LeedsLeedsUnited Kingdom
  2. 2.Department of Computer ScienceTechnical University of KaiserslauternKaiserslauternGermany
  3. 3.School of Computer Science and CommunicationKTH Royal Institute of TechnologyStockholmSweden

Bibliographic information