Transcript State of the Art and Future Trends in Geoinformatics

State of the Art and Future
Trends in Geoinformatics
Gerhard Navratil
[email protected]
Contents
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How to determine State of the Art?
GIS: The Early Years
Framework Changes
Changes in Research Questions
Future Challenges
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How to Determine State of the Art?
How to Determine Future Trends?
• Look at industry solutions?
• Look at publications in journals?
• Look at presentations in conferences?
• Look at the development of knowledge!
Try to extrapolate!
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GIS: The Early Years
1960‘s: First Steps of GIS
– Computers slow
– Storage media slow and
expensive (tapes)
– No graphical out put
Nixdorf 820, 1968 (Christian Giersing )
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Early Maps
(Marble et al. 1984)
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Early Topics
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Data storage
Networks and topology
Attribute modelling
Required functionality
User interface
Graphical output
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Example: Geometry
• Representation
– Vector: Spaghetti, Topology (1980‘s)
– Raster: Simple concept, easy to print, scanned maps
• Efficient storage
– Databases save space (relational DB) (Codd 1969)
• Problems of data combination
– Map algebra (Tomlin, 1990)
– Line intersection problem
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Example: Line Intersection
• It Makes Me so Cross (Douglas, 1974)
– Task: General purpose FORTRAN routine to
decide if two line segments intersect
– 5 pages of text, 21 special cases
• It Doesn‘t Make Me Nearly as Cross (Saalfeld,
1987)
– New representation (point-vector)
L  p0  r ( p1  p0 ), L'  p0 'r ' ( p1 ' p0 ' )
– determine r, r' – intersect if both in [0,1]
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What Happened?
Implementation led to problems
First solution
e-improvements?
Improvement by different approach
More elegant solution
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Framework Changes (80‘s/90‘s)
• Increasing amount of computing power
(from exclusive equipment to ubiquitous
infrastructure)
• Standard graphical user interfaces
GIS on standard office PC‘s
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Problem: Data Supply
Main data sources:
• Scanned maps (outdated)
• Measurements (slow, expensive)
• Satellite images (low resolution,
expensive)
• Aerial photography (required digitizing,
expensive)
 Standard Data Suppliers (e.g., Ordnance
Survey)
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Advantages of Standard Data
Sources
• Well developed data capture processes 
known quality
• Clear understanding of the limits of the
data
• (At least some) Liability issues solved
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Disadvantages of Standard Data
Sources
• Standard products with defined quality –
only limited options
• Dependency on a single data provider
• Market power of producers  Data quality
discussed from producer perspective only
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Software
Small number of commercial GIS:
• ESRI
• Intergraph
• Siemens
• MapInfo
• (Erdas)
Almost no independent products (mainly
GRASS and Spring)
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Recent Changes
• New communication technology (Internet,
mobile phones, WLAN)
• Abundant data:
– Volunteered Geographic Information (VGI)
– Satellite images
– Laser Scanning/Digital Photogrammetry
• Software producing communities (open
source software)
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New Tools/Environments
• GNSS: Positioning information is available
high level of quality
• Smartphones (mobile, bi-directional access
to data)
• Google Earth, Google Maps, Microsoft Bing
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Changes in Research Questions
• Quality of the new data?
• Users are no experts  Communication
with lay people
• Data used during execution of a process,
not during planning – changes?
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Research Questions on Data (1)
• Understanding the processes that produce
the data
– Quality checks? Consistency? Updates?
– Data processing steps?
• Understanding the communities providing
the data
– What is the incentive?
– What is the task for which the data is needed?
– Knowledge level of data producers?
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Research Questions on Data (2)
• Limitations of the data set?
– Scale of the data capture?
– What is the quality? Is it uniform?
• Connection between different data sets?
– Different communities collecting similar data
in the same region?
– Similar communities collecting similar data in
neighbouring region?
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Research Questions on Users
• What is the information needed by the
user?
– Required level of quality?
– Required additional information?
• How to best communicate the information?
– Graphical or Verbal or Oral?
– User-oriented or as a map?
– Level of redundancy?
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Example: OpenStreetMap (1)
• Data provided by
– Communities
– Organizations (e.g., Ordnance Survey)
– Private persons
• Data collected by
– GPS-tracks
– Digitizing aerial images
Teheran (OSM, 2011)
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Example: OpenStreetMap (2)
• Free to use (License: Creative Commons)
• Usable for routing
and mapping
• Available for
large parts of the
world
Public Transport in Berlin (Melchior Moos, 2008)
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Example: OpenStreetMap (3)
• User tasks
– Cartography (professionals/amateurs)
– Navigation (routing)
• Assessing the quality is difficult
– Attribute accuracy in international context?
– Completeness?
In comparison to what? NAVTEQ/TeleAtlasdata?
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Example: OpenStreetMap (4)
Classification in different countries,
e.g., highway = tertiary
(Google Earth)
(Wikipedia)
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Emerging Research Fields
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Semantics of data
Assessment of data quality for VGI
User interfaces
Processes and time
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Semantics of Data (1)
Data from different sources – what happens
when we combine them?
– Different communities use
different classifications –
land cover vs. land use?
– Comparing apples and
oranges?
(Comber, 2007)
(Wikipedia)
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Semantics of Data (2)
Current tool: Ontologies
Research questions:
• Semantics of processes
• Vagueness
• Translation of terms between domains
• Trust in semantic quality of VGI
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Assessment of Data Quality (1)
• Easy for result of single observation
(quality of equipment)
• Difficult if
– Data collected during extended period
e.g., land management
– Data collected by vast number of people
e.g., VGI
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Assessment of Data Quality (2)
Ideas for quality assessment in land
management:
• Geometrical quality of cadastral boundaries:
Compare data set with original surveys
(Navratil et al. 2010)
• Compare the data sets with orthophotos
Result:
• Varying quality – how to communicate?
• A: deviations between a few cm and 150m
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User Interfaces
• New impulses for interfaces from Google
Earth, smartphones, etc.
How to exert this?
• How to exploit the new hardware?
e.g., smartphones, tablets
• 2D or 3D? When to use what?
• Virtual reality or mixed reality?
Applications? Benefits? Realization?
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Processes and Time (1)
• Data are not static – reality changes
constantly  Data are connected to the
date of collection
• Data describe/are influenced by processes
e.g., sensor networks
• Consistency checks require combination
of processes and data
e.g., differential equations (Hofer & Frank 2009)
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Processes and Time (2)
Task are described by
• Location
• Duration
• Prerequisites
Coordination of tasks requires
• Start and end location of tasks
• Duration of navigation between different
locations
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Conclusions (1)
Finding research topics requires
• Understand the recent developments
• Detect changes in the framework
• Find the consequences of these changes
• Look for missing links
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Conclusions (2)
Future key research topics are
• Semantics of data
• Assessment of data quality for VGI
• User interfaces
• Processes and time
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