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Envisioning Information Lecture 9 – Time: Taxonomy & Techniques

Envisioning Information Lecture 9 – Time: Taxonomy & Techniques. Ken Brodlie kwb@comp.leeds.ac.uk. Many applications involve visualization of data over a period of time… … including the first visualization … and one of the most famous. Time.

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Envisioning Information Lecture 9 – Time: Taxonomy & Techniques

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  1. Envisioning Information Lecture 9 – Time: Taxonomy & Techniques Ken Brodlie kwb@comp.leeds.ac.uk ENV 2006

  2. Many applications involve visualization of data over a period of time… … including the first visualization … and one of the most famous Time ENV 2006

  3. We are familiar with time series in many walks of life… Today’s lecture looks at visualization and time Time Seismogram http://quake.utah.edu/helicorder/heli/yellowstone/index.html ENV 2006

  4. Data: D = {(t1,d1), (t2,d2), .. (tn,dn)} where di = f(ti) d can be multivariate Representations can be: Static Dynamic Types of time… Discrete or interval time Sequence of snapshots; or measured over interval such as days Linear or cyclic time Start to end; or repeating like the seasons Ordered or branching time Data values in strict time sequence; or branches with parallel time tracks Taxonomy (Frank/Mueller/Schumann) Visualization Methods for Time-dependent Data – An Overview : Mueller and Schumann See also: http://infovis.uni-konstanz.de/events/VisAnalyticsWs05/pdf/07MuellerSchumann.pdf ENV 2006

  5. Discrete Interval Discrete vs Interval Time ENV 2006

  6. Linear Previous examples were linear Cyclic Circle graphs (discrete) Sector graphs (interval) Linear vs Cyclic discrete interval ENV 2006

  7. Rather than a simple ordered sequence…. Scientists often experiment with simulations of processes Here a simulation is started and results obtained at a sequence of time steps… … but to investigate some feature in more detail, the scientist rolls back the simulation and restarts with a different parameter setting Ordered vs Branching Time ENV 2006

  8. Often we can use existing visualization techniques… and consider time as just any other variable.. New visual metaphors have also been suggested however… Visual Metaphors ENV 2006

  9. Parallel Coordinates for Time Series Data! Garnett, 1903 Statistical atlas, 12th census of US • Map different time steps to different axes Axes are years (right to left) Position on axis Is ranking ENV 2006

  10. Special techniques have been proposed for visualization over very long time periods Themeriver technique has been used to depict evolutionary behaviour… ..Bit like an interval time version of parallel coordinates?? Visual Metaphors : Long time periods Evolution of baby names.. .. Try it at: http://babynamewizard.com/namevoyager/lnv0105.html ENV 2006 Laura and Martin Wattenberg

  11. Themeriver • Themeriver for climate change… • … ENV 2006

  12. Taglines Visualizing tags attached to Flickr online image sharing Evolution over time Show tags that are specific to a time period Definition of ‘interesting’ is the following calculation: u = tag t = specified time period N(u,t) = no of occurrences of tag in period N(u) = total no of occurences of tag C = constant River Metaphor I(u,t) = N(u,t) / (C + N(u)) ENV 2006 http://research.yahoo.com/taglines/

  13. Jarke van Wijk has shown how visualization can be used in analysis of time series data Opposite is power demand within ECN (Netherlands Energy Research Centre)… … hard to pick out patterns of usage Cluster and Calendar based Visualization of Time Series Data ENV 2006

  14. Each day taken as an ‘observation’ and cluster analysis performed Take two ‘closest’ days and merge into an average day… … and keep repeating Cluster Approach dendogram Full cluster tree for energy data ENV 2006

  15. Then we are able to visualize the key patterns of use… … but better still, in next slide we link to a calendar Visualizing the Main Clusters ENV 2006

  16. Calendar View of Power Demand ENV 2006

  17. Calendar View of Number of Employees at Work http://www.win.tue.nl/~vanwijk/clv.pdf What can you observe? (NB Dec 5th) ENV 2006

  18. Timestore is a nice idea for organising mailboxes… Timestore Yiu, Baecker, Silver, Long U Toronto ENV 2006

  19. Spiral graphs are a space-efficient way of visualizing long time series… Spiral Graphs ENV 2006 From Alexa et al

  20. The Time Wheel allows several time series to be viewed simultaneously… … how successful is this? … rotation can help, why? … again cf parallel coordinates? Time Wheel Tominski, Abello, Schumann - Rostock ENV 2006

  21. MultiComb • Here is another idea from Rostock group – MultiComb • Two variations: Time axes as spokes Time axes as perimeter ENV 2006

  22. The 3D TimeWheel has time in central axis, variable axes on opposite end of slices… …wheel can open out TimeWheel in 3D ENV 2006

  23. MultiComb in 3D.. .. here there are 7 time series plots with a common time axis MultiComb in 3D ENV 2006

  24. Kiviat charts were used in parallel program performance visualization… … but are essentially star glyphs Here is a Kiviat Tube Star glyphs laid out along time axis and surface created Kiviat Tubes ENV 2006

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