env 20069.1 envisioning information lecture 9 – time: taxonomy & techniques ken brodlie...
TRANSCRIPT
ENV 2006 9.2
Time
• Many applications involve visualization of data over a period of time…
• … including the first visualization
• … and one of the most famous
ENV 2006 9.3
Time
• We are familiar with time series in many walks of life…
• Today’s lecture looks at visualization and time
http://quake.utah.edu/helicorder/heli/yellowstone/index.html
Seismogram
ENV 2006 9.4
Taxonomy (Frank/Mueller/Schumann)
• 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
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 9.5
Discrete vs Interval Time
• Discrete • Interval
ENV 2006 9.6
Linear vs Cyclic
• Linear– Previous examples were linear
• Cyclic– Circle graphs (discrete)
– Sector graphs (interval)
discrete
interval
ENV 2006 9.7
Ordered vs Branching Time
• 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
ENV 2006 9.8
Visual Metaphors
• Often we can use existing visualization techniques… and consider time as just any other variable..
• New visual metaphors have also been suggested however…
ENV 2006 9.9
Parallel Coordinates for Time Series Data!
• Map different time steps to different axes Garnett, 1903Statistical atlas,12th census of US
Axes are years(right to left)Position on axisIs ranking
ENV 2006 9.10
Visual Metaphors : Long time periods
• 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??
Evolution of baby names.... Try it at:http://babynamewizard.com/namevoyager/lnv0105.html
Laura and Martin Wattenberg
ENV 2006 9.11
Themeriver
• Themeriver for climate change…• …
ENV 2006 9.12
River Metaphor
• 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
http://research.yahoo.com/taglines/
I(u,t) = N(u,t) / (C + N(u))
ENV 2006 9.13
Cluster and Calendar based Visualization of Time Series Data
• 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
ENV 2006 9.14
Cluster Approach
• Each day taken as an ‘observation’ and cluster analysis performed
• Take two ‘closest’ days and merge into an average day…
• … and keep repeating
dendogram
Full cluster tree for energy data
ENV 2006 9.15
Visualizing the Main Clusters
• Then we are able to visualize the key patterns of use…
• … but better still, in next slide we link to a calendar
ENV 2006 9.16
Calendar View of Power Demand
ENV 2006 9.17
Calendar View of Number of Employees at Work
http://www.win.tue.nl/~vanwijk/clv.pdfWhat can you observe? (NB Dec 5th)
ENV 2006 9.18
Timestore
• Timestore is a nice idea for organising mailboxes…
Yiu, Baecker, Silver, LongU Toronto
ENV 2006 9.19
Spiral Graphs
• Spiral graphs are a space-efficient way of visualizing long time series…
From Alexa et al
ENV 2006 9.20
Time Wheel
• The Time Wheel allows several time series to be viewed simultaneously…
• … how successful is this?
• … rotation can help, why?
• … again cf parallel coordinates?
Tominski, Abello, Schumann - Rostock
ENV 2006 9.21
MultiComb
• Here is another idea from Rostock group – MultiComb• Two variations:
Time axes as spokes Time axes as perimeter
ENV 2006 9.22
TimeWheel in 3D
• The 3D TimeWheel has time in central axis, variable axes on opposite end of slices…
• …wheel can open out
ENV 2006 9.23
MultiComb in 3D
• MultiComb in 3D..
• .. here there are 7 time series plots with a common time axis
ENV 2006 9.24
Kiviat Tubes
• 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