Geovisualization1

1
Geovisualization1

• Human vision and domain expertise powerful tools
• 80 of all digital data generated today includes
  geospatial reference
• Magnitude and complexity of data sets on the rise
• Challenge how to transform these data sets into
  information and knowledge
• Geovisualization has potential to provide
  windows into complexity of phenomena and
  processes through innovative scene construction,
  virtual environments and collaboration, thus
  providing insight into structures and
  relationships contained with these data sets.

1 MacEachren, A. M., M. Kraak, 2001. Research
Challenges in Geovisualization, Cartography and
GIS, Vol. 28 No1, 2001 PP. 3-12 (extensive
paraphrasing and quoting)
2
Geo-visualization and Cartography

• Paper maps both database and presentation media
• Digital geography and GIS split the task
• digital map now seen as providing information
  access and knowledge construction activities as
  well as traditional presentation role.
• Modern cartography deals with complex issues of
  geo-spatial information organization, access and
  display.
• Geo-visualization is the highly interactive tool
  that facilitates the search for unknowns which
  supports information exploration and knowledge
  construction
• Its an active instrument in the users thinking
  process
• Its an invaluable tool for exploratory data
  analysis

3
Problem, Themes and Issues

• Current visualization methods and tools not
  designed to deal with unique geo-spatial
  characteristics of data
• Spatial data different
• Location using (e.g. X,Y Z)
• Location using place named features (e.g. highway
  66)
• Features and processes scale dependent
• Autocorrelation of spatial/temporal data
• Four primary themes for research
• Representation
• Integration with knowledge construction and
  geo-computing
• Interface design
• Cognition-usability

4
Representation

• Challenge posed by very large multivariate
  geo-spatial data sets that include both 3 spatial
  dimensions, a temporal dimension and a scale
  issue.
• Tools to respond to challenge interactivity,
  animation, hyper-linking immersive environments
  and dynamic object behaviors. pushing bounds of
  what is considered a map
• Five issues
• Semiotics and meaning how visual depiction
  relates to meaning
• Data how visual depiction relates to
  interpretation and structures imposed on data
• Map use how visual depiction relates to use
• Map users how visual depiction relates to
  human-computer interaction
• Technology how visual depiction can/should take
  advantage of technology

5
Representation Five challenge categories

• Develop theory for geo-presentation and
  formalizing representation methods
• Theory doesnt support realistic displays,
  immersive environments and flexible interaction
  with autonomous objects (with own behavior).
• Develop forms of representation that support the
  understanding of geo-spatial phenomena and
  space-time processes
• Imbue representational object with adaptive
  behaviors
• Adapt representative methods to meet changing
  nature of data to be represented.
• Large complex data sets that vary in certainty
  and depict processes over time
• Adapt representation to methods to the increasing
  range of tasks geo-visualization must support
• Knowledge discovery
• Decision making
• Recent technological developments
• Immersive environments mobile communication etc.

6
Visualization-computation Integration

• Challenge interaction among variables so complex
  that human vision cannot be successful in
  isolation.
• Integrate advantages of computational and visual
  approaches to facilitate knowledge construction
  from geo-spatial data.
• Goal of this integration is to visually enable
  knowledge construction tools that facilitate both
  the process of uncovering patterns and
  relationships in complex data and subsequent
  explanation of those patterns and relationships.
• Tool that can function in the absence of
  pre-determined hypotheses
• Exploratory visual analysis
• Visual approaches to data analysis
• Knowledge discovery in databases (KDD)
• Find useful valid structures in large volumes of
  data which provide meaning or explanation.
• Geocomputation
• Develop methods to model and analyze a range of
  highly complex often non-deterministic problems
  related to geo-spatial data

7
Visualization-computation Integration Challenges

• Develop visual approaches to geo-spatial data
  mining using visual methods for uncovering
  unknown patterns and relationships in large
  geo-spatial data-bases.
• What information represented (explicit
  incorporation of spatial and temporal aspects of
  data)
• How information represented (effect on human
  inference process/hypothesis building
• Integrate visual and computational tools that
  enable human and machines to collaborated in
  knowledge construction
• Human experts, human users and computational
  agents
• Engineering issues
• Develop computational architectures that support
  integrating databases with visualization
• General cross-cutting issue
• How to explicitly incorporate the location and
  time component of multivariate data within visual
  and analytic methods.
• How to include rich conceptual structure of
  geographic knoledge in computationally based
  models
• Incorporate geographic meaning within
  visualization environments

8
Interface

• Complementary advances are required in
  geo-visualization interface design
• Realize potential of geo-visualization to prompt
  creative thinking
• Do people think differently with computers
• Extend our understanding of metaphor for
  geo-visualization and develop principles for
  selection of appropriate metaphors
• Interface for digital earth
• Access to and visualization of massive databases
• Exploit landscape metaphors for providing this
  interface
• Extend understanding of interface design to take
  advantage of virtual environments
• Create comprehensive user-centered design
  approach to geo-visualization

9
Cognitive/Usability Issue

• Does the tool work and how?
• Can people deal with a full emersion environment
• Different people react differently to
  visualization environment
• Problem for geo-visualization is to understand
  (and take advantage of) the mechanism by which
  the dynamic, external visual representations
  offered by geo-visualization serve as prompts for
  the creation and use of mental representations.
• Lack of established paradigms for conduction
  cognitive or usability studies with highly
  interactive visual environments.

10
Cognitive/Usability Issue challenges

• Develop cognitive theory to support and assess
  usability of methods for geo-visualization within
  virtual environments
• Develop more effective interface metaphors and
  understand schema people use in working with
  metaphors
• Understand these in context of geo-visualization
  interface design
• Determine context in which geo-visualization is
  successful
• Facilitates science?
• Decision-making?
• Education?

11
Crosscutting Research Challenges

• Assumption of geo-visualization is that
  abstraction is essential for achieving insight
• Many systems use realism
• Explore tension between two
• Current methods and tools do not support
  effective representation or encoding of
  geographic knowledge and meaning thus knowledge
  construction using these tools cannot build
  easily from existing knowledge

12
My own beef

• Can we find patterns through geo-visualization
  that cant be obtained statistically?
• Would the creation of AAAs (autonomous, analytic
  agents) that move through time and space gather
  information that couldnt be obtained either
  through statistics or geo-visualizion