Domino

Extracting, Comparing, and Manipulating Subsets
across Multiple Tabular Datasets


Samuel Gratzl

Marc Streit

Nils Gehlenborg

Alexander Lex

Hanspeter Pfister
  music artists
artist origin career status gender first album studio albums
Rihanna Barbados active female 2005 7
Britney Spears US active female 1999 8
Whitney Houston US inactive female 1985 7
Eminem US active male 1996 8
Elton John UK active male 1969 33
Elvis Presley US inactive male 1956 25
The Beatles UK inactive group 1963 12
U2 Ireland active group 1980 12
ABBA Sweden inactive group 1973 8

Related Work

Flexible Linked Axes for Multi-variate Data Visualization

[Claessen and van Wijk, 2011]

Connected Charts: Explicit Visualization of Relationships between Data Graphics

[Viau and McGuffin, 2012]

  music artists
artist origin career status gender first album studio albums
Rihanna Barbados active female 2005 7
Britney Spears US active female 1999 8
Whitney Houston US inactive female 1985 7
Eminem US active male 1996 8
Elton John UK active male 1969 33
Elvis Presley US inactive male 1956 25
The Beatles UK inactive group 1963 12
U2 Ireland active group 1980 12
ABBA Sweden inactive group 1973 8
music markets (countries)
market continent sold singles sold albums retailvalue population
US North America 1.5M 225.8M 3635.2M$ 310.2M
Germany Europe 6.8M 98.7M 1713.6M$ 82.3M
UK Europe 2.4M 99.8M 1388.1M$ 62.3M
Australia Australia 0.0M 24.5M 408.0M$ 21.5M
Canada North America 0.2M 25.9M 343.2M$ 33.7M
Netherlands Europe 0.5M 16.7M 270.2M$ 16.8M
Austria Europe 0.1M 7.5M 184.1M$ 8.2M
Sweden Europe 0.1M 13.7M 136.8M$ 9.1M
Ireland Europe 0.2M 4.9M 77.9M$ 4.4M
  artists' number one hits per music market
US UK GER CAN AUS AUT IRE SWE NLD
Rihanna 13 8 5 9 8 5 6 3 1
Britney Spears 5 6 3 6 5 3 7 4 4
Whitney Houston 11 4 3 7 3 1 2 2 2
Eminem 5 8 3 4 8 4 7 4 2
Elton John 9 7 3 19 4 1 3 1 4
Elvis Presley 17 21 1 23 12 0 8 1 5
The Beatles 20 17 12 22 22 9 13 0 22
U2 2 7 0 14 5 1 19 0 3
ABBA 1 9 9 0 6 3 12 3 10

Domino

 
Analyse multiple tabular datasets by
 
comparing
manipulating
extracting
 
subsets
 

Domino Visualization Technique

basic elements:

  • blocks and their
  • relationships

representing:

  • subsets
  • associated data
  • and relationships between
population (million) retailvalue ($) sold albums (absolute) 310 300 250 200 150 100 50 0 0 1000 2000 3000 3635 226 200 150 100 50 0

Block Types

Partitioned Blocks Numerical Blocks Matrix Block artists countries
  • gender
  • origin
  • continent
  • age
  • album count
  • population
  •    # of #1 hits

Multiform Visualization

[Lex et al., 2011]

career status artist # of studio albums # of number one hits country continent
Patient
Gene
# mutations
age, gender, ...

[The Cancer Genome Atlas Research Network et al., 2014]

Relationships

None
  • <nothing>
Weak
  • shared item type
Medium
  • shared item type
  • shared partitioning
Strong
  • shared item type
  • shared partitioning
  • shared sorting

Relationships Representation

item group block
granularity
direction parallel
orthogonal
Parallel Coordinates

[Inselberg, 1985]

Scatterplot
Scatterplot Matrix (SPLOM)
Flexible Linked Axis

[Claessen and van Wijk, 2011]

Connected Charts

[Viau and McGuffin, 2012]

Parallel Sets

[Kosara etal, 2006]

Matchmaker

[Lex et al., 2010]

StratomeX

[Lex et al., 2012]

Music Use Case
Cancer Genomics Use Case

http://caleydo.org

Open Source (BSD 3)

Source code:
 https://github.com/caleydo
Demos, videos, and more:
 http://domino.caleydo.org

Placeholder + Live Previews

Selection and Highlighting

Subset Manipulation

Summary and Future Work

Domino is general visualization technique based on blocks and relationships for extracting, comparing and manipulating subsets.

Future Work

  • Guidance
  • Grammar

Guidance

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?
?
?
?
?
?
?
?

[Streit et al., 2014]

Grammar

Domino Grammar

+ axis = numerical_block shown_as "1D scatterplot"axis right_of axis connecting items

Domino

Extracting, Comparing, and Manipulating Subsets
across Multiple Tabular Datasets

Samuel Gratzl, Nils Gehlenborg, Alexander Lex, Hanspeter Pfister, and Marc Streit

samuel.gratzl@jku.at

domino.caleydo.org

github.com/caleydo

 caleydo.org     github.com/caleydo     twitter.com/caleydo_org

References

  1. [Claessen and van Wijk, 2011] J. H. Claessen and J. J. van Wijk, “Flexible Linked Axes for Multivariate Data Visualization,” IEEE Transactions on Visualization and Computer Graphics (InfoVis ’11), vol. 17, no. 12, pp. 2310–2316, 2011.
  2. [Viau and McGuffin, 2012] C. Viau and M. J. McGuffin, “ConnectedCharts: Explicit Visualization of Relationships between Data Graphics,” Computer Graphics Forum, vol. 31, no. 3pt4, pp. 1285–1294, 2012.
  3. [The Cancer Genome Atlas Research Network et al., 2014] The Cancer Genome Atlas Research Network et al., “Integrated Genomic Characterization of Papillary Thyroid Carcinoma“, Cell 159, 676–690, 2014.
  4. [Inselberg, 1985] A. Inselberg, “The plane with parallel coordinates”, The Visual Computer 1, 69–91, 1985.
  5. [Kosara etal, 2006] R. Kosara, F. Bendix, and H. Hauser, “Parallel Sets: Interactive Exploration and Visual Analysis of Categorical Data,” IEEE Transactions on Visualization and Computer Graphics, vol. 12, no. 4, pp. 558–568, 2006.
  6. [Lex et al., 2010] A. Lex, M. Streit, C. Partl, K. Kashofer, and D. Schmalstieg, “Comparative Analysis of Multidimensional, Quantitative Data,” IEEE Transactions on Visualization and Computer Graphics  (InfoVis ’10), vol. 16, no. 6, pp. 1027–1035, 2010.
  7. [Lex et al., 2011] A. Lex, M. Streit, H.-J. Schulz, C. Partl, D. Schmalstieg, 2011. VisBricks: Multiform Visualization of Large, Inhomogeneous Data. IEEE Transactions on Visualization and Computer Graphics (InfoVis ’11) 17, 2291–2300, 2011
  8. [Lex et al., 2012] A. Lex, M. Streit, H.-J. Schulz, C. Partl, D. Schmalstieg, P. J. Park, and N. Gehlenborg, “StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization” Computer Graphics Forum (EuroVis ’12), vol. 31, no. 3, pp. 1175–1184, 2012.
  9. [Streit et al., 2014] M. Streit, A. Lex, S. Gratzl, C. Partl, D. Schmalstieg, H. Pfister, P.J. Park, N. Gehlenborg, “Guided visual exploration of genomic stratifications in cancer”. Nature Methods 11, 884–885, 2014.