Abstraction Requirements in
Geospatial Applications
•
Werner Kuhn
Muenster Semantic Interoperability Lab (MUSIL)
eScience Theme 4: Spatial Semantics
Why we need data for analysis
Acquiring remotely sensed data
Modelling it with in-situ data
Mapping it by Census zone
Calculating mortality rates
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Programming Abstractions in GIS
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Some classical GI computations
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Overlay
Buffer
Map (=raster) algebra
(map) generalization
Terrain analysis (viewshed, watershed)
Network analyses (shortest path etc.)
Image analysis (filter, object recognition etc.)
Separate world: application models, simulations
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My take on „Programming Abstractions“
¾ Programs = Algorithms + Data Structures
¾ Programming Abstractions =
Algorithm Abstractions
+ Data Models
¾ GIS has overwhelmingly emphasized Data
Models
• Raster
• Vector (topological)
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Abstractions in GIS Standards
¾ The Open Geospatial Consortium (OGC) has
produced and enabled technology to share and reuse
geospatial information
¾ This has grown the GI business substantially
¾ Geospatial information is vastly used in all areas of
society
¾ Spatial Data Infrastructures (SDI) are emerging at
local, regional, national, international, global levels
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OpenGIS (OGC) Specifications
¾ WMS
¾ WFS
¾ WCS
¾ GML
¾ SLD
¾ Filter
¾ Catalog
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¾ WCTS
¾ Grid Coverages
¾ Location Services
¾ Simple Features
• CORBA
• SQL
• OLE/COM
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What is a Spatial Data Infrastructure
¾ A framework of data, technology, policies, standards, and
human resources, necessary to facilitate the sharing and
using of geographic information.
• The term infrastructure is used to
emphasise not just hardware and data
(equivalent in the rail system to carriages,
power lines, rail tracks, stations) but also
the need for coordinating structures and
international standards and agreements
(on gauges, timetables, safety rules,
signalling, etc.) without which the system
cannot operate consistently and safely.
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Programming Abstractions in GIS
http://europa.tiscali.it/futuro/speciali/quiz_giovani/374123859quiz.html
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Why do we need such
infrastructure?
Regional policy
Impacts
Agriculture
Transport
Environment
Research
¾ Increasing shift from sector-based (silos)
policy making towards more integrated,
cross-sectoral approaches.
http://www.wintermantel-lagersysteme.de/uploads/pics/IndustrieSilos.jpg
Werner Kuhn
Programming Abstractions in GIS
• This new approach
particularly
important for
environmental
policy
• But very difficult to
get to work across
sectors and
boundaries
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Good policy must be based on sound
knowledge
Information needs for flood and drought forecasting:
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Meteorological
• Rainfall
• Temperature
• evapotranspiration
Hydrological
• river courses
• cross sections
• observed discharges and water levels
• location of lakes, incl. size & water levels
• hydropower reservoirs, polders
soil data
• texture and depth to bedrock
• soil hydraulic parameters
land use data
• type
• coverage during the year
• Population
• Economic value of properties
topographical data
• elevation
• location and height of dykes
• critical infrastructure (hospitals,
power stations, elderly homes)
70% of all fresh water bodies in Europe
are part of a trans-boundary river basin !!
INSPIRE Directive
¾ INSPIRE lays down general rules to establish an
infrastructure for spatial information in Europe for the
purposes of Community environmental policies and
policies or activities which may have an impact on the
environment.
¾ INSPIRE does not require collection of new spatial data
¾ INSPIRE does not affect Intellectual Property Rights or
Licensing conditions
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INSPIRE Components
¾ Metadata
¾ Interoperability of spatial data sets and services
¾ Network services (discover, view, download, invoke)
¾ Data and Service sharing (policy)
¾ Coordination and measures for Monitoring & Reporting
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INSPIRE Spatial Data Scope
Annex I
1.
2.
3.
4.
5.
6.
7.
8.
9.
Annex II
Coordinate reference systems
Geographical grid systems
Geographical names
Administrative units
Addresses
Cadastral parcels
Transport networks
Hydrography
Protected sites
1.
2.
3.
4.
Elevation
Land cover
Ortho-imagery
Geology
Harmonised spatial data specifications more
stringent for Annex I and II than for Annex III
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INSPIRE Thematic Scope
Annex III
1.
2.
3.
4.
5.
6.
Statistical units
Buildings
Soil
Land use
Human health and safety
Utility and governmental
services
7. Environmental monitoring
facilities
8. Production and industrial
facilities
9. Agricultural and
aquaculture facilities
10. Population distribution –
demography
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11. Area management/restriction
/regulation zones & reporting
units
12. Natural risk zones
13. Atmospheric conditions
14. Meteorological geographical
features
15. Oceanographic geographical
features
16. Sea regions
17. Bio-geographical regions
18. Habitats and biotopes
19. Species distribution
20. Energy Resources
21. Mineral resources
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Composite Service
plant ID
457
Input
Leakage
Information
plant location
R: 3405138
H: 5760997
Get Plant
Location
Get Nearest
Airport
airport code
FMO
emission rate
29 mg/s
Get Wind
dispersion map
Create Gas
Dispersion Map
Calculate Gas
Dispersion
Plume
wind report
XML...
plume
GML...
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OGC Web Processing Service (WPS)
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OWS-4 test bed on WPS
The OWS-4 project introduced three geospatial services that were
implemented as WPS processes:
• Generalization
• Clipping
• Binary Grid Processing Service
Two other services were not implemented as WPS processes but
could have been, namely:
• Feature Fusion Service (FFS)
• Topological Quality Assessment Service (TQAS)
A service providing a spatial intersection of two GML themes is
available via http://geotech.lih.rwth-aachen.de/wpsclient/
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SWOT of current GI abstractions
¾ Strengths
• Take up of GI, „data interoperability“
¾ Weaknesses
• transfers of large data sets, data separated from
operations, processing remains monolithic and proprietary
¾ Opportunities
• API‘s, mashups, microformats, processing service
abstractions
¾ Threats
• schema exposure in GML, complexity
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Some Insights from a Met Office report
¾ “Interoperability cannot be achieved by definition of an
application schema alone”
¾ “A set of well defined service interfaces are vital to
ensure that data can be accessed in an
implementation agnostic fashion”
¾ “There is no mechanism allowing the description of
operations that a feature can invoke / be invoked on it.”
¾ „alternative schema do not naturally co-exist since they
essentially divide the world up using different aspects
of the problem ... “
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Current major semantics challenges
1. Describing services (e.g. for WPS)
2. Linking ontologies
3. Modeling similarity
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The predominant GI view
geo-atom = < x, Z, z(x) >
er
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in
n
io
t
a
et
r
p
in
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r
Spatial Reference Systems
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pr
et
at
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???
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Vision
Users of geographic information should be
able to refer thematic data to semantic
reference systems, just as they refer
geometric data to spatial reference systems.
Software should support the
¾ referencing and grounding process
¾ projections to simpler semantic spaces
¾ semantic translation among different
reference systems
¾ similarity measurement
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Ontologies
#| ATKIS-Objektartenkatalog (ATKIS-OK) | Seite Blatt | Stand
|
#| Teil D1: ATKIS-OK 25
| 62.1 1 ( 2) | 01.11.1995 |
#|______________________________________|________________|____________|
#| Nr. Objektbereich | Nr. Objektgruppe
|
#| 6000 RELIEF
| 6200 Besondere Geländeoberflächenformen
|
#|____________________|_______________________________________________|
#| Nr. Objektart
| Nr. |
#| 6201 Damm, Wall, Deich
| 6201 |
#|_____________________________________________________________|______|
Werner Kuhn
CAP landuse code
CAP landuse label
1
Urban
1.A
Urban; Residential
1.A.0.a
Urban; Residential; Single family
...
...
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Some Research Challenges
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Upper level geo-ontology
Ontology of GI computations
Specifying functionality (of services)
Exploit user communities as data providers
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Some implementation challenges
¾ Package GIS functionality as web services
¾ Capture their semantics in catalogues
¾ Evolve the technology in a „Google world“
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Conclusions
¾ Processing styles around GI
• In good old GIS
• Web services (largely data serving so far)
• Web processing services: only recently specified
• API‘s of the Google maps type
¾ Semantics is the frontier for GI
• application vocabularies (= domain ontologies)
• semantic reference systems
• will need to bring processes back in (but said this for 15 years)
¾ A bottom-up revolution is happening
• user-generated GI
• APIs for mash-ups
• GI business shifts from authorites to communities
¾ Our major enemy: complexity (and being proud of)
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Thank You !
Email to
kuhn@uni-muenster.de
MUSIL (Muenster Semantic Interoperability Lab)
http://musil.uni-muenster.de
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