A Matter of Time and Interactions: Interactively Exploring Time-Oriented Data Silvia Miksch Vienna University of Technology Institute of Software Technology and Interactive Systems (ISIS)
Jan 02, 2016
A Matter of Time and Interactions: Interactively Exploring Time-Oriented Data
Silvia MikschVienna University of TechnologyInstitute of Software Technology and Interactive Systems (ISIS)
Data types
1-dimensional
2-dimensional
3-dimensional
Temporal
Multi-dimensional
Tree
Network
= 4D space“the world we are living in”
[Shneiderman, 1996]
Spatial + temporal dimensions
Every data element we measure is related and often only meaningful in context ofspace + time
Example: price of a hotelwhere?
when?
Differences between space and time
Space can be traversed “arbitrarily”we can move back to where we came from
Time is unidirectionalwe can’t go back or forward in time
Humans have senses for perceiving spacevisually, touch
Humans don’t have senses for perceiving time
Visual Analytics of Time-Oriented Data
visualizing time-oriented data 2interacting with time 3analyzing time-oriented data
automated analysis4
characterizing time & time-oriented data
modeling timemodeling time-oriented data
1
Modelling time
Modelling time
Example:Granularity paradoxon
Modelling time-oriented data
Modelling data & time
Visual Analytics of Time-Oriented Data
visualizing time-oriented data 2interacting with time 3analyzing time-oriented data
automated analysis4
characterizing time & time-oriented data
modeling timemodeling time-oriented data
1
Visualizing time
Time → Time (Animation) Time → Space
Visual variables: position, length, angle, slope, connection, thickness, ...
Visualizing time-oriented data
specific techniques+
concepts, frameworks
Visualizing time-oriented data
specific techniques+
concepts, frameworks
Visualizing time-oriented data
specific techniques+
concepts, frameworks
Visualizing time-oriented data
specific techniques+
concepts, frameworks
Visual Analytics of Time-Oriented Data
visualizing time-oriented data 2interacting with time 3analyzing time-oriented data
automated analysis4
characterizing time & time-oriented data
modeling timemodeling time-oriented data
1
Interaction facilitates active discourse with the data and visualization
see think
modify
[Card et al., 1983]
Interaction Levels
Physical LevelHow does the user physically interact?E.g., Mouse Wheel, Touch Screen Interaction Devices
Control LevelHow can it be carried out by the user?E.g., Move Scrollbar User Interface
Conceptual LevelWhat to be done?E.g., Scrolling / Navigating Task
[Aigner; Presentation 2009]
Taxonomies :: low-level interactions[Yi, Kang, Stasko 2007]
Taxonomies :: dimensions, operators, & user tasks
[Yi, Kang, Stasko 2007]
Additional task taxonomies [McEachren 1995] [Andrienko & Andrienko 2006]
Interaction :: user intents
Select: mark something as interesting
Explore: show me something else
Reconfigure: show me a different arrangement
Encode: show me a different representation
Abstract/Elaborate: show me more or less detail
Filter: show me something conditionally
Connect: show me related items
Undo/Redo: Let me go to where I have been already
Change configuration: Let me adjust the interface
Based on 1) [Yi et al., 2007]
Users & Tasks
User-Centered Design
representation &
interaction
data
task user
expr
essi
vene
ss effectiveness
appropriateness
Interacting with time
specific interaction techniques+
task & interaction taxonomies
[VisuExplore project]
Interacting with time
specific interaction techniques+
task & interaction taxonomies
[VisuExplore project]
[VisuExplore project: measure tool]
Interacting with time
specific interaction techniques+
task & interaction taxonomies
[CHI09 workshop, VisuExplore project]
[Animated Scatterplot project]
Interacting with time
specific interaction techniques+
task & interaction taxonomies
[CHI09 workshop, VisuExplore project]
[CareCruiser project]
Visual Analytics of Time-Oriented Data
visualizing time-oriented data 2interacting with time 3analyzing time-oriented data
automated analysis4
characterizing time & time-oriented data
modeling timemodeling time-oriented data
1
Computational analysis of time-oriented data
temporal data-abstraction
statistics
temporal data-mining
[MuTIny, DisCo project]
visualizing time-oriented data 2interacting with time 3analyzing time-oriented data
automated analysis4
characterizing time & time-oriented data
modeling timemodeling time-oriented data
1
Visual Analytics of Time-Oriented Data
1. What has to be presented?
– Time and data!2. Why has it to be presented?
– User tasks!3. How is it presented?
– Visual representation!
[Aigner, Miksch Schumann, Tominski,
2011]
Forthcoming Book 2011
Aigner, Miksch Schumann, Tominski, 2011
Visualization of Time-Oriented Time
Compared: 75 methods
DataVariables: univariate vs. multivariateFrame of reference: abstract vs. spatial
TimeArrangement: linear vs. cyclicTime primitive: instant vs. interval
VisualizationMapping: static vs. dynamicDimensionality: 2D vs. 3D
[Aigner, Miksch Schumann, Tominski,
2011]
Compared: 75 methods
DataVariables: univariate vs. multivariateFrame of reference: abstract vs. spatial
TimeArrangement: linear vs. cyclicTime primitive: instant vs. interval
VisualizationMapping: static vs. dynamicDimensionality: 2D vs. 3D
[Aigner, Miksch Schumann, Tominski,
2011]
Thanks to
Wolfgang Aigner (Danube Universty Krems, VUT)Alessio Bertone (Danube Universty Krems)Tim Lammarsch (Danube Universty Krems, VUT)Alexander Rind (Danube Universty Krems) Thomas Turic (Danube Universty Krems)
Heidrun Schumann (University of Rostock)Christian Tominski (University of Rostock)
Bilal Alsallakh (CVAST, Vienna University of Technology)Theresia Gschwandtner (CVAST, Vienna University of Technology)Klaus Hinum (Vienna University of Technology)Katharina Kaiser (CVAST, Vienna University of Technology) Margit Pohl (CVAST, Vienna University of Technology)Markus Rester (Vienna University of Technology)