Vizbi 2012 Takeaway

Vizbi Takeaway 2012 Visualising biological data - highlights

Vizbi Takeaway 2012 - visualising biological data

Photo: avlxyz - http://www.flickr.com/photos/avlxyz/3786955645/

Monday, 2 April 2012

http://www.flickr.com/photos/avlxyz/3786955645/

http://www.flickr.com/photos/avlxyz/3786955645/


Visualising biological data

Photos: francisrowland / SéanO / Siemar | Flickr

6 - 8 March 2012 EMBL Heidelberg

300 participants, 80 posters, 25 talks, 12 tutorials


http://www.flickr.com/photos/francisrowland/

http://www.flickr.com/photos/francisrowland/

http://www.flickr.com/photos/73754179@N05/

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http://www.flickr.com/photos/javiersierra/1335605035/

http://www.flickr.com/photos/javiersierra/1335605035/


Takeaway menu

• Juri Pärn - The curse of n-dimensions

• Ingvar Lagerstedt - The power of images

• Martijn van Iersel - Pathway visualisation & WikiPathways

• Glen van Ginkel - Principles of data visualisation

• Francis Rowland - UX design for data visualisation

• Benedetta Baldi - Data visualisation technology for biologists



The curse of n-dimensionsJuri Pärn EMBL-EBI External Services

One dimension...

1

2

3



The curse of n-dimensions

Two dimensions...

1 2

3 4



The curse ofn-dimensions...

Three dimensions...



• With every new dimension, it gets worse

• The diagonal grows slowly but steadily with

• For dimension = 100 the diagonal is

• Important to keep in mind for clustering, as many clustering algorithms use euclidian distance

• Points tend to cluster along dimensions, not across dimensions

• Possible solution for clustering

- dimension reduction

- using another distant function, e.g.




an example...




The power of imagesIngvar Lagerstedt PDBe

How do you read a paper?

• Title

• Author

• Abstract

• Images/Tables

• Legends for images/table

• Conclusions

• Methods/Body of text



Using images effectively

• What do you want to show?

• Highlight/simplify

- remove details that are not relevant to the point you want to make

• We are not all layout designers

- use professional help

- I tend to cram in far to much detail

• Publishers often charge per image

- encourages composite images



Example from Nature Structural& Molecular Biology



Colouring

• Use limited number of colours

- Horror example with 250+ colour based keys

- Think hard if you really need more than say 5-6 colours

• Use soft colours for large areas

- It is fine to use strong colours for features/lines etc., but they tend to be tiring if used excessively

• Think about the colour blind



Designing a new file format (RNA)

• Many existing competing compact formats

• Wanted a new community based

• Everyone likes XML

• parsers are free

• Except

• There was 30 X bloat

• Details were left ambiguous

• Each group produced slightly different versions

• Hardly anyone can cope with reading other groups version



Pathway Visualization & WikiPathwaysMartijn van Iersel Saez-Rodriguez Group

http://www.wikipathways.org





Editing pathways



26

90

1

5

26

90

15

Pathways

Genes



Simple Macro

moleculeCatalysis

Clone

Systems Biology Graphical Notation (SBGN)



LibSBGN

ReferencePathVisio

Rend. Ext.SBGN-ED



Principles & Resource sharingGlen van Ginkel PDBe

Cross-Origin Resource Sharing (CORS)

http://www.w3.org/TR/cors/

https://developer.mozilla.org/en/HTTP_access_control

Domain A http://domaina.example

Domain B http://domainb.foo

XMLHttpRequest








https://developer.mozilla.org/en/TTP_access_control

https://developer.mozilla.org/en/TTP_access_control


Graphics & visualisation

• Graphics used to form a sign system:

- Each mark (point, line, or area) represents a data element

- Visualisation is about choosing visual variables to encode relationships between data elements

- difference, similarity, order, proportion

- only position supports all relationships • Huge range of alternative visual encodings for

data

- find images that express and effectively convey the information

Prof Jessie Kennedy (Institute for Informatics & Digital Innovation)



Encoding schemes

Adapted from Mackinlay J (1986) Automating the design of graphical presentations of relational information.



Accuracy of Quantitative Perceptual Tasks

Cleveland, W.S. & McGill, R. Science 229, 828–833 (1985).



Mapping data types to encoding

Mackinlay J (1986) Automating the design of graphical presentations of relational information.



Colour

• “Above all, do no harm”

• colour can cause the wrong information to stand out and

• make meaningful information difficult to see.

“Colour used poorly is worse than no colour at all”- Edward Tufte



Brewer Palettes

Brewer palettes (colorbrewer.org) provide a range of palettes based on HSV model which make life easier for us….

Avoid the use of hue to encode quantitative variables

QUALITATIVE SEQUENTIAL DIVERGING



UX design for data visualisation

Data vizexpertsBiologists

Designers

Francis Rowland EMBL-EBI External Services

Data visualisationsweet spot



Tell the story of your research through data visualisation

Biologists

Data visualisation experts

Integrate analysis & visualisation

Designers

Apply design principles and expertise



Data visualisation technology for biologistsBenedetta Baldi Computational Neurobiology

autoFill



Simulation Animation

Eric Keller



autoFill http://autofill.grahamj.com/


http://autofill.grahamj.com/

http://autofill.grahamj.com/


Drew Berry

Questions?



Thanks to...

Scientific Organisers:

Seán O’Donoghue CSIRO and Garvan Institute, Australia

James Procter University of Dundee, UK

Conference Organiser:

Anja Maria Kröffges EMBL Heidelberg, Germany

Continue the discussion on the EBI Interfaces mailing list:

http://listserver.ebi.ac.uk/mailman/listinfo/interfaces




Vizbi 2012 Takeaway

Design

Transcript of Vizbi 2012 Takeaway