strabon semantic support for eo data access in...
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Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
June 23 Florence, Italy
Strabon
Semantic support for EO Data Access in TELEIOS
Dept. of Informatics and Telecommunications National and Kapodistrian University of Athens
Presenter: George Garbis
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Outline
Motivation
Representing and Querying Geospatial and Temporal Information in RDF
Applications
The Fire Monitoring Service of the National Observatory of Athens
The TerraSAR-X Virtual Observatory of the German Aerospace Center
Thoughts for discussion
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Catalogue
Processing Chains
EO data center
Archive
State of the Art in EO Data Centers
Raw Data
Users
EOWEB
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Example
Can I pose the following query using EOWEB?
Find images taken by the SEVIRI satellite on August 25, 2007 which contain fire hotspots in areas which have been classified as forests according to CORINE Land Cover, and are located within 2km from an archaeological site in the Peloponnese.
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Example (cont’d)
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Example (cont’d)
Well, only partially.
Find images taken by the SEVIRI satellite on August 25, 2007 which contain fire hotspots in areas which have been classified as forests according to CORINE Land Cover, and are located within 2km from an archaeological site in the Peloponnese.
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Example (cont’d)
But why?
All this information is available in the satellite images and other auxiliary data sources of EO data centers or on the Web.
However, EO data centers today do not allow:
mining of satellite image content and
its integration with other relevant data sources so the previous query can be answered.
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High Level Data Modeling
Need for representing
Standard product metadata
Standard product semantic annotations
Geospatial information
Temporal information
Need to link to other data sources
GIS data
Other information on the Web
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Semantics-Based Representation and Querying of EO Data
The data model stRDF and the query language stSPARQL
The system Strabon
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Outline
Motivation
Representing and Querying Geospatial and Temporal Information in RDF
Applications
The Fire Monitoring Service of the National Observatory of Athens
The TerraSAR-X Virtual Observatory of the German Aerospace Center
Conclusions
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RDF: Resource Description Framework
W3C recommendation
RDF is a graph data model ( + XML syntax + semantics)
For representing metadata
For describing the semantics of information in a machine-readable way
Resources are described in terms of properties and property values using RDF statements
Statements are represented as triples, consisting of a subject, predicate and object.
11
"23.7636"^^xsd:double noa:hasArea
ex:BurntArea1
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The Data Model stRDF
stRDF stands for spatial/temporal RDF.
It is an extension of the W3C standard RDF for the representation of geospatial data that may change over time.
stRDF extends RDF with:
Spatial literals encoded in OGC standards Well-Known Text or GML
New datatypes for spatial literals (strdf:WKT, strdf:GML and strdf:geometry)
Temporal literals can be either periods or instants
New datatype for temporal literals (strdf:period)
Placed as the fourth component of a triple to denote valid time
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stRDF: An example (1/2)
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stRDF: An example (1/2)
ex:BurntArea1
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stRDF: An example (1/2)
rdf:type ex:BurntArea1
noa:BurntArea
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stRDF: An example (1/2)
“1” ^^xsd:int noa:hasID
rdf:type ex:BurntArea1
noa:BurntArea
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stRDF: An example (1/2)
“1” ^^xsd:int
"23.7636"^^xsd:double noa:hasArea
noa:hasID
rdf:type ex:BurntArea1
noa:BurntArea
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"POLYGON(( 38.16 23.7, 38.18 23.7, 38.18
23.8, ... 38.16 23.8, 38.16 3.7));
<http://spatialreference.org/ref/epsg/4121/>"
^^strdf:WKT
stRDF: An example (1/2)
“1” ^^xsd:int
"23.7636"^^xsd:double noa:hasArea
noa:hasID
rdf:type ex:BurntArea1
noa:BurntArea
geo:geometry
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"POLYGON(( 38.16 23.7, 38.18 23.7, 38.18
23.8, ... 38.16 23.8, 38.16 3.7));
<http://spatialreference.org/ref/epsg/4121/>"
^^strdf:WKT
stRDF: An example (1/2)
Spatial Data Type Well-Known Text
“1” ^^xsd:int
"23.7636"^^xsd:double noa:hasArea
noa:hasID
rdf:type ex:BurntArea1
noa:BurntArea
geo:geometry
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"POLYGON(( 38.16 23.7, 38.18 23.7, 38.18
23.8, ... 38.16 23.8, 38.16 3.7));
<http://spatialreference.org/ref/epsg/4121/>"
^^strdf:WKT
stRDF: An example (1/2)
Spatial Data Type Well-Known Text
“1” ^^xsd:int
"23.7636"^^xsd:double noa:hasArea
noa:hasID
rdf:type ex:BurntArea1
noa:BurntArea
geo:geometry
Spatial Literal (OpenGIS Simple
Features)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:hasGeometry ?RGEO .
?R noa:hasCorineLandCoverUse . .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:hasGeometry ?CGEO .
?BA rdf:type noa:BurntArea .
?BA geo:hasGeometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)}
• Find all burned forests within 10kms of a city
stSPARQL: An example (1/2)
Spatial Functions (OGC Simple Feature Access)
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stSPARQL: An example (1/2)
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stRDF: An example (2/2)
clc:region1 clc:hasLandCover clc:Forest clc:region1 clc:hasLandCover clc:Forest .
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stRDF: An example (2/2)
clc:region1 clc:hasLandCover clc:Forest
"[2006-08- 25T11:00:00+02,2007-08-25T11:00:00+02)"^^strdf:period . clc:region1 clc:hasLandCover clc:Forest .
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stRDF: An example (2/2)
clc:region1 clc:hasLandCover clc:Forest
"[2006-08- 25T11:00:00+02,2007-08-25T11:00:00+02)"^^strdf:period .
noa:ba1 rdf:type noa:BurntArea
"[2007-08-25T11:00:00+02,2009-08-25T11:00:00+02)"^^strdf:period .
clc:region1 clc:hasLandCover clc:Forest .
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stRDF: An example (2/2)
clc:region1 clc:hasLandCover clc:Forest
"[2006-08- 25T11:00:00+02,2007-08-25T11:00:00+02)"^^strdf:period .
noa:ba1 rdf:type noa:BurntArea
"[2007-08-25T11:00:00+02,2009-08-25T11:00:00+02)"^^strdf:period .
clc:region1 clc:hasLandCover clc:AgriculturalArea
"[2009-08-25T11:00:00+02, "UC")"^^strdf:period .
clc:region1 clc:hasLandCover clc:Forest .
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:geometry ?RGEO ;
?R noa:hasCorineLandCoverUse ?F ?t1. .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:geometry ?CGEO .
?BA rdf:type noa:BurntArea ?t2.
?BA geo:geometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)
FILTER( strdf:during(?t1, “[2006-01-01:00:00:01,
2006-01-01:23:59:59]”^^strdf:period)) &&
strdf:before(?t1, ?t2) }
Find all areas that were forests in 2006 and got burned later within 10kms of a city
stSPARQL: An example (2/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:geometry ?RGEO ;
?R noa:hasCorineLandCoverUse ?F ?t1. .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:geometry ?CGEO .
?BA rdf:type noa:BurntArea ?t2.
?BA geo:geometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)
FILTER( strdf:during(?t1, “[2006-01-01:00:00:01,
2006-01-01:23:59:59]”^^strdf:period)) &&
strdf:before(?t1, ?t2) }
Find all areas that were forests in 2006 and got burned later within 10kms of a city
stSPARQL: An example (2/2)
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SELECT ?BA ?BAGEO
WHERE { ?R rdf:type noa:Region .
?R geo:geometry ?RGEO ;
?R noa:hasCorineLandCoverUse ?F ?t1. .
?F rdfs:subClassOf clc:Forests .
?CITY rdf:type dbpedia:City .
?CITY geo:geometry ?CGEO .
?BA rdf:type noa:BurntArea ?t2.
?BA geo:geometry ?BAGEO .
FILTER( strdf:intersect(?RGEO,?BAGEO) &&
strdf:distance(?RGEO,?CGEO,uom:km)<10)
FILTER( strdf:during(?t1, “[2006-01-01:00:00:01,
2006-01-01:23:59:59]”^^strdf:period)) &&
strdf:before(?t1, ?t2) }
Find all areas that were forests in 2006 and got burned later within 10kms of a city
stSPARQL: An example (2/2)
Temporal extension functions
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stSPARQL: An example (2/2)
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stSPARQL: More details
We start from SPARQL 1.1.
We add a SPARQL extension function for each function defined in the OGC standard OpenGIS Simple Feature Access – Part 2: SQL option (ISO 19125) for adding geospatial data to relational DBMSs and SQL.
We add a set of temporal functions (superset of Allen’s functions) as SPARQL extension functions
We add appropriate geospatial and temporal extensions to SPARQL 1.1 Update language
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stSPARQL vs. GeoSPARQL
GeoSPARQL is a recent OGC standard to develop an extension of SPARQL for querying geospatial data expressed in RDF.
stSPARQL and GeoSPARQL have been developed independently.
stSPARQL geospatial query functionality is very close to a subset of GeoSPARQL:
Core
Geometry extension
Geometry topology extension
GeoSPARQL goes beyond stSPARQL: binary topological relations as RDF properties (spatial reasoners)
Additional stSPARQL features:
Geospatial aggregation functions
Temporal literals
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Strabon: A Scalable Geospatial RDF Store
stRDF graphs
stSPARQL/ GeoSPARQL
queries
WKT GML
Query Engine
Parser
Optimizer
Evaluator
Transaction
Manager
Storage Manager
Repository
SAIL
RDBMS
Strabon
GeneralDB
Sesame
PostgreSQL
PostgreSQL Temporal
PostGIS
http://bit.ly/Strabon
Period
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Outline
Motivation
Representing and Querying Geospatial and Temporal Information in RDF
Applications
The Fire Monitoring Service of the National Observatory of Athens
The TerraSAR-X Virtual Observatory of the German Aerospace Center
Conclusions
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Processing Chain (SciQL based)
HotSpots
Back End: MonetDB / Strabon
Use Case I: Real-Time Fire Monitoring (NOA)
41 7/1/2013
Data Vault
Eumetsat @ 9.5°East
Raw Data
• CORINE Landcover • Admin Boundaries • POIs
External Sources
• Search & Display
• Search for raw & Processing
• Real-time Fire Monitoring
• Refinement (Post-Processing)
• Linked Data
Geospatial Ontology
Web access based on Semantics
Linked Geospatial Data
Semantic technologies
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NOA Ontology
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NOA Ontology
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Linked Geospatial Data
Datasets that we published as linked data:
CORINE Land Use / Land Cover
Coastline of Greece
Greek Administrative Geography
Portal: http://www.linkedopendata.gr/
Datasets from Linked Open Data Cloud
OpenStreetMap
GeoNames
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Linked Open Data Cloud
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Linked Open Data Cloud
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Linked Open Data GeoNames
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Linked Open Data OpenSteetMap
Published by LinkedGeoData
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Linked Open Data Greek Administrative Geography
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Linked Open Data CORINE Land Use / Land Cover
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Linked Open Data Coastline
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Improvements
http://bit.ly/StrabonDemo
Semantic Enrichment for hotspots
Increase Accuracy by correlating with linked geospatial data
Generating Rapid Mapping products
Validating the results of the automatic annotation process by correlating them with auxiliary linked geospatial data
Assisting the training process by providing the user with contextual information about the area of interest
DEMO!
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Semantic Enrichment for Hotspots
Enrich hotspot products
1. Connect each hotspot with a municipality that it is located
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Semantic Enrichment for Hotspots
Enrich hotspot products
1. Connect each hotspot with a municipality that it is located
Improve accuracy with respect to underlying area
2. Eliminate false alarms in sea
3. Keep land part of the polygon
4. Eliminate false alarms in inconsistent land cover areas
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Semantic Enrichment for Hotspots
Enrich hotspot products
1. Connect each hotspot with a municipality that it is located
Improve accuracy with respect to underlying area
2. Eliminate false alarms in sea
3. Keep land part of the polygon
4. Eliminate false alarms in inconsistent land cover areas
Improve accuracy with respect to temporal persistence of each hotspots
5. Remove “Christmas tree” effects
”Christmas tree effect”: some hotspots appear in a timestamp, in the next timestamp they disappear, then they re-appear again, and so on.
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Improve the accuracy of EO data
Correlate fire products with auxiliary data to increase their thematic accuracy e.g., delete the parts of the polygons that fall into the sea.
DELETE {?h noa:hasGeometry ?hGeo}
INSERT {?h noa:hasGeometry ?dif}
WHERE {
SELECT DISTINCT ?h ?hGeo
(strdf:intersection(?hGeo, strdf:union(?cGeo)) AS ?dif)
WHERE {
?h rdf:type noa:Hotspot.
?h strdf:hasGeometry ?hGeo.
?c rdf:type coast:Coastline.
?c strdf:hasGeometry ?cGeo.
FILTER( strdf:anyInteract(?hGeo, ?cGeo)}
GROUP BY ?h ?hGeo
HAVING strdf:overlap(?hGeo, strdf:union(?cGeo))}
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Improve the accuracy of EO data
Correlate fire products with auxiliary data to increase their thematic accuracy e.g., delete the parts of the polygons that fall into the sea.
DELETE {?h noa:hasGeometry ?hGeo}
INSERT {?h noa:hasGeometry ?dif}
WHERE {
SELECT DISTINCT ?h ?hGeo
(strdf:intersection(?hGeo, strdf:union(?cGeo)) AS ?dif)
WHERE {
?h rdf:type noa:Hotspot.
?h strdf:hasGeometry ?hGeo.
?c rdf:type coast:Coastline.
?c strdf:hasGeometry ?cGeo.
FILTER( strdf:anyInteract(?hGeo, ?cGeo)}
GROUP BY ?h ?hGeo
HAVING strdf:overlap(?hGeo, strdf:union(?cGeo))}
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Generating Rapid Mapping Products ZKI (Center for Satellite Based Crisis Information)
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Generating Rapid Mapping Products ZKI (Center for Satellite Based Crisis Information)
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Improvements
http://bit.ly/DemoSextant
Semantic Enrichment for hotspots
Increase Accuracy by correlating with linked geospatial data
Generating Rapid Mapping products
Validating the results of the automatic annotation process by correlating them with auxiliary linked geospatial data
Assisting the training process by providing the user with contextual information about the area of interest
DEMO!
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Generating Rapid Mapping Products: Sextant
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Generating Rapid Mapping Products: Sextant
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Outline
Motivation
Representing and Querying Geospatial and Temporal Information in RDF
Applications
The Fire Monitoring Service of the National Observatory of Athens
The TerraSAR-X Virtual Observatory of the German Aerospace Center
Conclusions
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Metadata (xml annotation file)
Use Case II: A Virtual Observatory for TerraSAR-X data (DLR)
INSPIRE Conference 2013: Building Virtual Earth Observatories Using Scientific Database, Semantic Web and Linked Geospatial Data
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Metadata (xml annotation file)
Use Case II: A Virtual Observatory for TerraSAR-X data (DLR)
INSPIRE Conference 2013: Building Virtual Earth Observatories Using Scientific Database, Semantic Web and Linked Geospatial Data
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Improvements
Semantic Enrichment for hotspots
Increase Accuracy by correlating with linked geospatial data
Generating Rapid Mapping products
Validating the results of the automatic annotation process by correlating them with auxiliary linked geospatial data
Assisting the training process by providing the user with contextual information about the area of interest
DEMO!
http://bit.ly/DLRDemo
67 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discovery Queries
Select all patches corresponding to the class Water
SELECT ?g (GROUP_CONCAT(?annotation; separator=", ") AS
?labels)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo dlr:Water .
FILTER (strdf:anyInteract(?g, "POLYGON ((12.301451
45.40493,12.398127 45.416817,12.386066
45.46502,12.289288 45.45313,12.301451
45.40493))"^^strdf:WKT)) .
}
GROUP BY ?g
68 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discovery Queries
Select all patches corresponding to the class Water
SELECT ?g (GROUP_CONCAT(?annotation; separator=", ") AS
?labels)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo dlr:Water .
FILTER (strdf:anyInteract(?g, "POLYGON ((12.301451
45.40493,12.398127 45.416817,12.386066
45.46502,12.289288 45.45313,12.301451
45.40493))"^^strdf:WKT)) .
}
GROUP BY ?g
69 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discovery Queries
Select all patches corresponding to the class Water and its subclasses
SELECT ?g (GROUP_CONCAT(?annotation; separator=", ") AS
?labels)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
?annotation rdfs:subClassOf dlr:Water .
FILTER (strdf:anyInteract(?g, "POLYGON ((12.301451
45.40493,12.398127 45.416817,12.386066 45.46502,12.289288
45.45313,12.301451 45.40493))"^^strdf:WKT)) .
}
GROUP BY ?g
70 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discovery Queries
Select all patches corresponding to the class Water and its subclasses
SELECT ?g (GROUP_CONCAT(?annotation; separator=", ") AS
?labels)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
?annotation rdfs:subClassOf dlr:Water .
FILTER (strdf:anyInteract(?g, "POLYGON ((12.301451
45.40493,12.398127 45.416817,12.386066 45.46502,12.289288
45.45313,12.301451 45.40493))"^^strdf:WKT)) .
}
GROUP BY ?g
71 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discover Correlation Between Datasets (1/2)
List the labels of all patches that are inside each CORINE Land Use/Land Cover class
SELECT DISTINCT ?clcLandUse ?annotation ?g
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
FILTER(strdf:anyInteract(?g, "POLYGON ((…))"^^strdf:WKT)).
?clc rdf:type ?clcType .
?clc teleios:hasCode ?clcCode .
?clcteleios:hasID ?clcID .
?clc teleios:hasGeometry ?clcG .
?clc teleios:hasLandUse teleios:continuousUrbanFabri.
FILTER(strdf:anyInteract(?clcG,"POLYGON((…))"^^strdf:WKT)).
FILTER (geof:sf-contains(?clcG, ?g)) . }
72 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discover Correlation Between Datasets (1/2)
List the labels of all patches that are inside each CORINE Land Use/Land Cover class
SELECT DISTINCT ?clcLandUse ?annotation ?g
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
FILTER(strdf:anyInteract(?g, "POLYGON ((…))"^^strdf:WKT)).
?clc rdf:type ?clcType .
?clc teleios:hasCode ?clcCode .
?clcteleios:hasID ?clcID .
?clc teleios:hasGeometry ?clcG .
?clc teleios:hasLandUse teleios:continuousUrbanFabri.
FILTER(strdf:anyInteract(?clcG,"POLYGON((…))"^^strdf:WKT)).
FILTER (geof:sf-contains(?clcG, ?g)) . }
?clcLandUse ?annotation
clc:coastalLagoons
dlr:Bouy, dlr:Water, dlr:Boat, dlr:RiverDeposit, dlr:Bridge, dlr:UrbanBuildUp, dlr:Agriculture, dlr:Vegetation, dlr:Cemetery
clc:seaAndOcean dlr:BreakingWave, dlr:Water
clc:continuousUrbanFabric dlr:UrbanBuildUp, dlr:Vegetation, dlr:Building
clc:discontinuousUrbanFabric
dlr:UrbanBuildUp, dlr:Vegetation, dlr:Building
… …
73 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discover Correlation Between Datasets (1/2)
List the labels of all patches that are inside each CORINE Land Use/Land Cover class
SELECT DISTINCT ?clcLandUse ?annotation ?g
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
FILTER(strdf:anyInteract(?g, "POLYGON ((…))"^^strdf:WKT)).
?clc rdf:type ?clcType .
?clc teleios:hasCode ?clcCode .
?clcteleios:hasID ?clcID .
?clc teleios:hasGeometry ?clcG .
?clc teleios:hasLandUse teleios:continuousUrbanFabri.
FILTER(strdf:anyInteract(?clcG,"POLYGON((…))"^^strdf:WKT)).
FILTER (geof:sf-contains(?clcG, ?g)) . }
?clcLandUse ?annotation
clc:coastalLagoons
dlr:Bouy, dlr:Water, dlr:Boat, dlr:RiverDeposit, dlr:Bridge, dlr:UrbanBuildUp, dlr:Agriculture, dlr:Vegetation, dlr:Cemetery
clc:seaAndOcean dlr:BreakingWave, dlr:Water
clc:continuousUrbanFabric dlr:UrbanBuildUp, dlr:Vegetation, dlr:Building
clc:discontinuousUrbanFabric
dlr:UrbanBuildUp, dlr:Vegetation, dlr:Building
… …
74 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
List the labels of all OpenStreetMap classes that are inside a patch SELECT ?annotation (GROUP_CONCAT(DISTINCT ?lgdType) AS ?lgdTypes)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
FILTER (strdf:anyInteract(?g, "POLYGON ((...))"^^strdf:WKT)) .
?lgd lgdont:directType ?lgdDirectType .
OPTIONAL { ?lgd a ?lgdType .
FILTER((?lgdType!=lgdont:Node)&&(?lgdType !=?lgdDirectType)) .}
?lgd lgdgeo:geometry ?lgdGeo .
FILTER(strdf:anyInteract(?lgdGeo, "POLYGON ((...))"^^strdf:WKT)) .
FILTER (geof:sf-contains(?g, ?lgdGeo)) .
}
GROUP BY ?annotation
ORDER BY ?annotation
Discover Correlation Between Datasets (2/2)
74
75 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
List the labels of all OpenStreetMap classes that are inside a patch SELECT ?annotation (GROUP_CONCAT(DISTINCT ?lgdType) AS ?lgdTypes)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
FILTER (strdf:anyInteract(?g, "POLYGON ((...))"^^strdf:WKT)) .
?lgd lgdont:directType ?lgdDirectType .
OPTIONAL { ?lgd a ?lgdType .
FILTER((?lgdType!=lgdont:Node)&&(?lgdType !=?lgdDirectType)) .}
?lgd lgdgeo:geometry ?lgdGeo .
FILTER(strdf:anyInteract(?lgdGeo, "POLYGON ((...))"^^strdf:WKT)) .
FILTER (geof:sf-contains(?g, ?lgdGeo)) .
}
GROUP BY ?annotation
ORDER BY ?annotation
Discover Correlation Between Datasets (2/2)
75
76 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
List the labels of all OpenStreetMap classes that are inside a patch SELECT ?annotation (GROUP_CONCAT(DISTINCT ?lgdType) AS ?lgdTypes)
WHERE {
?p rdf:type dlr:Patch .
?p dlr:hasGeometry ?g .
?p dlr:hasLabel ?l .
?l rdf:type dlr:Label .
?l dlr:correspondsTo ?annotation .
FILTER (strdf:anyInteract(?g, "POLYGON ((...))"^^strdf:WKT)) .
?lgd lgdont:directType ?lgdDirectType .
OPTIONAL { ?lgd a ?lgdType .
FILTER((?lgdType!=lgdont:Node)&&(?lgdType !=?lgdDirectType)) .}
?lgd lgdgeo:geometry ?lgdGeo .
FILTER(strdf:anyInteract(?lgdGeo, "POLYGON ((...))"^^strdf:WKT)) .
FILTER (geof:sf-contains(?g, ?lgdGeo)) .
}
GROUP BY ?annotation
ORDER BY ?annotation
Discover Correlation Between Datasets (2/2)
76
77 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Conclusions
We developed the data model stRDF and the query language stSPARQL for representing and querying geospatial data that may change over time
The Fire Monitoring Service of the National Observatory of Athens
The TerraSAR-X Virtual Observatory of the German Aerospace Center
78 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Discussion
Use higher-level languages, stop worrying about how to store and manage metadata, just focus on the actual processing
Express common earth observation operations easily using the stSPARQL/GeoSPARQL queries instead of using a lengthy C program
Rapid prototyping without the need to recompile everything
Integration with publically available linked open geospatial data
79 Exploiting the Integration Potential of Semantic Web and Linked Data Technologies for Geospatial Applications, Workshop in INSPIRE Conference 2013
Thank you for your attention!
Questions?
79
Strabon http://strabon.di.uoa.gr Manolis Koubarakis, Kostis Kyzirakos, Manos Karpathiotakis, Charalampos Nikolaou, Giorgos Garbis, Konstantina Bereta, Kallirroi Dogani, Stella Giannakopoulou and Panayiotis Smeros.
Mercurial repository: http://hg.strabon.di.uoa.gr Trac: http://bug.strabon.di.uoa.gr Mailing list: http://cgi.di.uoa.gr/~mailman/listinfo/strabon-users Continuous integration server http://test.strabon.di.uoa.gr/cis
Sextant: A web tool for browsing and mapping Linked Geospatial Data
http://test.strabon.di.uoa.gr/sextant/