Topological and Statistical Methods for Complex Data

Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces

  • Janine Bennett
  • Fabien Vivodtzev
  • Valerio Pascucci
Conference proceedings

Part of the Mathematics and Visualization book series (MATHVISUAL)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Large-Scale Data Analysis: In-Situ and Distributed Analysis

    1. Front Matter
      Pages 1-1
    2. Cyrus Harrison, Jordan Weiler, Ryan Bleile, Kelly Gaither, Hank Childs
      Pages 3-19
    3. Alejandro Ribés, Benjamin Lorendeau, Julien Jomier, Yvan Fournier
      Pages 21-37
    4. C. Seshadhri, Ali Pinar, David Thompson, Janine C. Bennett
      Pages 39-54
  3. Large-Scale Data Analysis: Efficient Representation of Large Functions

    1. Front Matter
      Pages 55-55
    2. Julien Tierny, David Günther, Valerio Pascucci
      Pages 57-71
    3. Léo Allemand-Giorgis, Georges-Pierre Bonneau, Stefanie Hahmann, Fabien Vivodtzev
      Pages 73-91
    4. Silvia Biasotti, Andrea Cerri, Michela Spagnuolo, Bianca Falcidieno
      Pages 93-107
  4. Multi-Variate Data Analysis: Structural Techniques

    1. Front Matter
      Pages 109-109
    2. Lars Huettenberger, Christoph Garth
      Pages 125-141
    3. Anne Berres, Hans Hagen, Stefanie Hahmann
      Pages 143-163
  5. Multi-Variate Data Analysis: Classification and Visualization of Vector Fields

    1. Front Matter
      Pages 165-165
    2. Attila Gyulassy, Harsh Bhatia, Peer-Timo Bremer, Valerio Pascucci
      Pages 205-218
  6. High-Dimensional Data Analysis: Exploration of High-Dimensional Models

    1. Front Matter
      Pages 219-219
    2. Mohamed S. Ebeida, Scott A. Mitchell, Anjul Patney, Andrew A. Davidson, Stanley Tzeng, Muhammad A. Awad et al.
      Pages 221-238
    3. Faniry Razafindrazaka, Konrad Polthier
      Pages 239-252
  7. High-Dimensional Data Analysis: Analysis of Large Systems

    1. Front Matter
      Pages 253-253
    2. Eleanor Anthony, Sheridan Grant, Peter Gritzmann, J. Maurice Rojas
      Pages 255-277
    3. Patricia J. Crossno, Timothy M. Shead, Milosz A. Sielicki, Warren L. Hunt, Shawn Martin, Ming-Yu Hsieh
      Pages 279-294
  8. Back Matter
    Pages 295-297

About these proceedings


This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013. It features the work of some of the most prominent and recognized leaders in the field who examine challenges as well as detail solutions to the analysis of extreme scale data.


The book presents new methods that leverage the mutual strengths of both topological and statistical techniques to support the management, analysis, and visualization of complex data. It covers both theory and application and provides readers with an overview of important key concepts and the latest research trends.


Coverage in the book includes multi-variate and/or high-dimensional analysis techniques, feature-based statistical methods, combinatorial algorithms, scalable statistics algorithms, scalar and vector field topology, and multi-scale representations. In addition, the book details algorithms that are broadly applicable and can be used by application scientists to glean insight from a wide range of complex data sets.


Data Analysis High-Dimensional Data Large-Scale Data Statistics Topology

Editors and affiliations

  • Janine Bennett
    • 1
  • Fabien Vivodtzev
    • 2
  • Valerio Pascucci
    • 3
  1. 1.Sandia National Laboratories, MS 9152LivermoreUSA
  2. 2.CEA CESTA, CS 60001Le Barp CEDEXFrance
  3. 3.School of Computing and SCI InstituteUniversity of UtahSalt Lake CityUSA

Bibliographic information