Part 1: Network Visualisation Tim Dwyer tim.dwyer@monash.edu - - PowerPoint PPT Presentation

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Part 1: Network Visualisation Tim Dwyer tim.dwyer@monash.edu - - PowerPoint PPT Presentation

Aug 07, 2023 378 likes •991 views

Part 1: Network Visualisation Tim Dwyer tim.dwyer@monash.edu ialab.it.monash.edu/~dwyer/ Monash University, Australia October 2019 projects.icij.org/ panama-papers/ power-players Atlas of economic complexity Network Earth Keystone taxa as

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Part 1: Network Visualisation

Tim Dwyer tim.dwyer@monash.edu ialab.it.monash.edu/~dwyer/ Monash University, Australia October 2019

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projects.icij.org/ panama-papers/ power-players

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Atlas of economic complexity

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Network Earth

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Keystone taxa as drivers of microbiome structure and functioning, Banerjee et al. 2018

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Credits

Kim Marriott Michael Wybrow Steve Kieffer Karsten Klein Uni Konstanz Chunlei Chang Vahan Yoghourdjian General Assembly Nathalie Henry Riche Microsoft Research Benjamin Bach Uni Edinburgh Kun-Ting Chen Graeme Gange Peter Stuckey Yalong Yang, Harvard Yehuda Koren Google Bongshin Lee Microsoft Research Sheelagh Carpendale Simon Fraser Uni George Robertson Microsoft Research

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Tim Dwyer, Yehuda Koren, and Kim Marriott. "IPSep-CoLa: An incremental procedure for separation constraint layout of graphs." IEEE Transactions on Visualization and Computer Graphics 12.5 (2006): 821-828.

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Stress majorization

stress(X)

(x,y)* x* y* x* y*

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Constrained stress majorization

 Instead of solving unconstrained quadratic forms we

solve subject to separation constraints

 i.e. Quadratic Programming stress(X)

x* y* x* y* (x,y)*

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Gradient projection

  • g
  • αg

x0 x1

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  • αg

x1

Gradient projection

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d x2 x1 β d

Gradient projection

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x*

Gradient projection

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Tim Dwyer, Yehuda Koren IEEE Symposium on Information Visualization, 2005. INFOVIS 2005, 65-72

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Separation Constraints

x1 + d ≤ x2 y1 + d ≤ y2

(x1,y1) (x2,y2) (x3,y3) w1 w2 h2 h3

x1 + ≤ x2 (w1+w2) 2 y3 + ≤ y2 (h2+h3) 2

Fast node overlap removal T Dwyer, K Marriott, PJ Stuckey International Symposium on Graph Drawing, 153-164, 2005

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“Unix” Graph data From www.graphviz.org

IPSep-CoLa

Tim Dwyer, Yehuda Koren, and Kim Marriott. "IPSep-CoLa: An incremental procedure for separation constraint layout of graphs." IEEE Transactions on Visualization and Computer Graphics 12.5 (2006): 821-828.

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Topology preserving constrained graph layout T Dwyer, K Marriott, M Wybrow International Symposium on Graph Drawing, 230-241, 2008

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https://ialab.it.monash.edu/webcola

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Tim Dwyer, Network Visualization as a Higher-Order Visual Analysis Tool IEEE computer graphics and applications 36(6), pp. 78-85, 2016.

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Dwyer, Tim, Nathalie Henry Riche, Kim Marriott, and Christopher Mears. "Edge compression techniques for visualization of dense directed graphs." IEEE transactions on visualization and computer graphics 19, no. 12 (2013): 2596-2605.

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Dwyer, Tim, Nathalie Henry Riche, Kim Marriott, and Christopher Mears. "Edge compression techniques for visualization of dense directed graphs." IEEE transactions on visualization and computer graphics 19, no. 12 (2013): 2596-2605.

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23 Edges

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17 Edges

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9 Edges

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7 Edges

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Improved Optimal and Approximate Power Graph Compression for Clearer Visualisation of Dense Graphs T Dwyer, C Mears, K Morgan, T Niven, K Marriott, M Wallace Pacific Visualization Symposium (PacificVis), 2014 IEEE, 105-112

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Yoghourdjian, V., Dwyer, T ., Gange, G., Kieffer, S., Klein, K., & Marriott, K. High-quality ultra-compact grid layout of grouped networks. IEEE Transactions on Visualization and Computer Graphics, 22(1), 339-348. 2015

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Kieffer, S., Dwyer, T., Marriott, K., & Wybrow, M. Hola: Human-like orthogonal network layout. IEEE transactions on visualization and computer graphics, 22(1), 349-358. 2015

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  • E. coli PPI

Vahan Yoghourdjian, Tim Dwyer, Karsten Klein, Kim Marriott, and Michael Wybrow Graph Thumbnails: Identifying and Comparing Multiple Graphs at a Glance IEEE Transactions on Visualization and Computer Graphics, 2018

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Vahan Yoghourdjian, Tim Dwyer, Karsten Klein, Kim Marriott, and Michael Wybrow Graph Thumbnails: Identifying and Comparing Multiple Graphs at a Glance IEEE Transactions on Visualization and Computer Graphics, 2018

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Hard Easy

Density Τ (|𝐹| |𝑊|) = 2 Density = 4 Density = 6 Nodes (|𝑊|)

Hardness model Graph size Local measures Clutter (crossings) Cognitive Scalability of Network Visualisation Vahan Yoghourdjian, Yalong Yang, Lee Lawrence, Michael Wybrow, Tim Dwyer, Kim Marriott

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Part 2: Immersive Analytics Interactive data analysis using the surfaces and spaces around us

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Credits

Maxime Cordeil

Andrew Cunningham

UniSA Yalong Yang Peter Hoghton Kim Marriott Bruce Thomas UniSA

Tobias Czauderna

Matthias Klapperstueck Benjamin Bach Falk Schreiber Bernie Jenny Sarah Goodwin Barrett Ens

Niklas Elmqvist

Uni Maryland

Andrea Batch Uni Maryland

Benjamin Lee

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64

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65

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Immersive Analytics Goals: to remove barriers betwe ween people, , their data and the tools they use fo for analysis to support data understanding and decision making everywh where and by everyone to make embodied tools that are intuitive, , engaging, , and make the best possible use of all sensory channels. . Immersive Analytics is the use of engaging, embodied analysis tools to support data understanding and decision making.

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Immersive Analytics Timeline

2014 2015 2016 2017

Feb. Mar. Jun. Oct. Nov. Oct. Nov. Dec.

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Immersive Analytics Timeline

2018 2019

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Immersive Analytics Book

Marriott, Dwyer, Schreiber, Thomas, Klein, Steurzlinger, Itoh, Riche Eds.

  • 1. What is Immersive Analytics?
  • 2. Time to Reconsider the Value of 3D for Information Visualisation
  • 3. Multisensory Immersive Analytics
  • 4. Interaction for Immersive Analytics
  • 5. Immersive Human-Centered Computational Analytics
  • 6. Immersive Visual Data Stories
  • 7. Situated Analytics
  • 8. Collaborative Immersive Analytics
  • 9. Just 5 Questions: toward a design framework for Immersive Analytics
  • 10. Immersive Analytics Applications in Life and Health Sciences
  • 11. Exploring Immersive Analytics For Built Environments

Published 2018

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Immersiv ive Analy lytic ics s Resea earch at Mo Monash

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Cordeil, Dwyer, Klein, Laha, Marriott, Thomas IEEE Transactions on Visualization and Computer Graphics 2016

Immersive Collaborative Analysis of Network Connectivity: CAVE-style or Head-Mounted Display?

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Colla llaboratio ion: Positions and movements

HMDs records

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Colla llaboratio ion: Positions and movements

CAVE2 records

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ImAxes: Immersive axes as embodied affordances for interactive multivariate data visualisation. Cordeil, M., Cunningham, A., Dwyer, T ., Thomas, B. H., & Marriott, K. In Proc. ACM Symp. on User Interface Software and Technology (pp. 71-83). ACM UIST 2017

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CHLORIDES DENSITY RESIDUAL SUGARS ACIDITY

Multidimensional data

VOLATILE ACIDITY FIXED ACIDITY ALCOHOL TYPE SULFUR DIOXIDE QUALITY SULPHATES

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Parallel coordinates Scatterplot Matrix

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Axes as embodied* affordances**

* Dourish, P. (2004) ** DA Norman (2002)

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83

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There Is No Spoon: Evaluating Performance, Space Use, and Presence with Expert Domain Users in Immersive Analytics. Batch A, Cunningham A, Cordeil M, Elmqvist N, Dwyer T, Thomas BH, Marriott K. IEEE Transactions on Visualization and Computer Graphics, 2019

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86

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In-Situ Mixed Reality Data Visualisation