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State of the Art and Future Trends in Geoinformatics
Gerhard Navratil
Gerhard Navratil 2/34
Contents
• How to determine State of the Art?
• GIS: The Early Years
• Framework Changes
• Changes in Research Questions
• Future Challenges
Gerhard Navratil 3/34
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!
Gerhard Navratil 4/34
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
• 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)
– determine r, r' – intersect if both in [0,1]
)''('''),( 010010 pprpLpprpL
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What Happened?
Implementation led to problems
First solution
Improvement by different approach
More elegant solution
-improvements?
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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Main data sources:• Scanned maps (outdated)• Measurements (slow, expensive)• Satellite images (low resolution,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 availablehigh 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?
Gerhard Navratil 20/34
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 routingand mapping
• Available forlarge parts of theworld 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/TeleAtlas-data?
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Example: OpenStreetMap (4)
Classification in different countries,e.g., highway = tertiary
(Wikipedia) (Wikipedia)(Google Earth)
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Emerging Research Fields
• 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 andoranges?
(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
Gerhard Navratil 29/34
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 orthophotosResult:• Varying quality – how to communicate?• A: deviations between a few cm and 150m
Gerhard Navratil 30/34
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?
Gerhard Navratil 31/34
Processes and Time (1)
• Data are not static – reality changes constantly Data are connected to the date of collection
• Data describe/are influenced by processese.g., sensor networks
• Consistency checks require combination of processes and datae.g., differential equations (Hofer & Frank 2009)
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Processes and Time (2)
Task are described by• Location• Duration• PrerequisitesCoordination 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