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TRIDEC and REVEAL projects: Geoparsing and Geosemantic knowledge model for trust and credibility analysis

Large-scale geoparsing of social media content and a geosemantic knowledge model for trust and credibility analysis. Original presentation was given to the OGC GeoSemantics Domain Working Group Meeting June 2014. Author: Stuart E. Middleton, University of Southampton IT Innovation Centre, UK

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REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium 
Your Name – Your Company 
your@email 
www.yourwebsite.com 
TRIDEC and REVEAL projects 
Stuart E. Middleton 
University of Southampton IT Innovation Centre 
sem@it-innovation.soton.ac.uk 
www.it-innovation.soton.ac.uk
REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium 
Overview 
1 
Overview of project use cases [TRIDEC, REVEAL] 
Architecture and use of standards 
Geoparsing and geosemantic annotation 
Geosemantic knowledge model for trust and credibility analysis 
Conclusions
REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium 
Overview of project use cases 
2 
FP7 TRIDEC project [Sept 2010 - Oct 2013] 
Natural Disasters 
Tsunami Early Warning Centres 
Landslides 
Flooding 
Twitter 
Social Media 
In-Situ Sensors 
Tide gauges 
GPS sensors 
Seismic sensors 
Data Fusion 
Geoparsing 
Alerting 
Decision Support 
Crisis Mapping 
Pattern Matching 
Modelling 
Command and Control
REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium 
Overview of project use cases 
3 
FP7 TRIDEC project [Sept 2010 - Oct 2013] 
Natural Disasters 
Tsunami Early Warning Centres 
Landslides 
Flooding 
Twitter 
Social Media 
In-Situ Sensors 
Tide gauges 
GPS sensors 
Seismic sensors 
Data Fusion 
Geoparsing 
Alerting 
Decision Support 
Crisis Mapping 
Pattern Matching 
Modelling 
Command and Control
REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium 
Overview of project use cases 
4 
FP7 REVEAL project [Nov 2013 – Oct 2016] 
News Events 
Journalists 
Breaking News 
Twitter 
Social Media 
User forums 
Data Fusion 
Geoparsing 
Decision Support 
Crisis Mapping 
Provenance 
Linked Data 
You Tube 
Instagram 
Four Square 
Geo Semantics 
Natural Language Processing 
Signature detection 
Verification
REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium 
Overview of project use cases 
5 
FP7 REVEAL project [Nov 2014 – Oct 2017] 
News Events 
Journalists 
Breaking News 
Twitter 
Social Media 
User forums 
Data Fusion 
Geoparsing 
Decision Support 
Crisis Mapping 
Provenance 
Linked Data 
You Tube 
Instagram 
Four Square 
Geo Semantics 
Natural Language Processing 
Signature detection 
Verification 
Trust 
Credibility
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TRIDEC and REVEAL projects: Geoparsing and Geosemantic knowledge model for trust and credibility analysis

  • 1. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Your Name – Your Company your@email www.yourwebsite.com TRIDEC and REVEAL projects Stuart E. Middleton University of Southampton IT Innovation Centre sem@it-innovation.soton.ac.uk www.it-innovation.soton.ac.uk
  • 2. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Overview 1 Overview of project use cases [TRIDEC, REVEAL] Architecture and use of standards Geoparsing and geosemantic annotation Geosemantic knowledge model for trust and credibility analysis Conclusions
  • 3. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Overview of project use cases 2 FP7 TRIDEC project [Sept 2010 - Oct 2013] Natural Disasters Tsunami Early Warning Centres Landslides Flooding Twitter Social Media In-Situ Sensors Tide gauges GPS sensors Seismic sensors Data Fusion Geoparsing Alerting Decision Support Crisis Mapping Pattern Matching Modelling Command and Control
  • 4. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Overview of project use cases 3 FP7 TRIDEC project [Sept 2010 - Oct 2013] Natural Disasters Tsunami Early Warning Centres Landslides Flooding Twitter Social Media In-Situ Sensors Tide gauges GPS sensors Seismic sensors Data Fusion Geoparsing Alerting Decision Support Crisis Mapping Pattern Matching Modelling Command and Control
  • 5. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Overview of project use cases 4 FP7 REVEAL project [Nov 2013 – Oct 2016] News Events Journalists Breaking News Twitter Social Media User forums Data Fusion Geoparsing Decision Support Crisis Mapping Provenance Linked Data You Tube Instagram Four Square Geo Semantics Natural Language Processing Signature detection Verification
  • 6. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Overview of project use cases 5 FP7 REVEAL project [Nov 2014 – Oct 2017] News Events Journalists Breaking News Twitter Social Media User forums Data Fusion Geoparsing Decision Support Crisis Mapping Provenance Linked Data You Tube Instagram Four Square Geo Semantics Natural Language Processing Signature detection Verification Trust Credibility
  • 7. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Architecture and use of standards 6 W3C Standards Sensor data  Semantic Sensor Network Ontology (SSNO) Communities  Semantically-Interlinked Online Communities (SIOC) Semantic Web, Linked Data  RDF, OWL OGC Standards Sensors  SensorML, SOS, SPS Geometry  OpenGIS, GeoSPARQL Other Open Street Map (OSM)  OSM entities and tags including OpenGIS
  • 8. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Architecture and use of standards 7 Scalable architecture for geosemantic processing Storm framework – scalable clustered deployment of processing bolts HTTP endpoints – control storm topologies in real-time RabbitMQ – communication backbone Database layer PostgreSQL + PostGIS database + planet OSM tables OWLIM SE (under evaluation)
  • 9. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geoparsing and geosemantic annotation 8 Exploiting OSM entity model as a knowledge-base planet_osm_line  roads, rivers ... planet_osm_point  bus stops, small buildings, stations ... planet_osm_polygon  admin areas, large buildings, parks ... All with OSM tags and OpenGIS geometry But ... 2+ trillion nodes impossible to hold in memory !! Use spatial filtering based on dynamically declared focus areas Compile inverted indexes and use information retrieval (IR) techniques
  • 10. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geoparsing and geosemantic annotation 9 Real-time geoparsing of social media streams PostGIS spatial filtered lookups for focus area (e.g. a city boundary) Compile an in-memory cache of location data Loop in real-time Match location name tokens to social media JSON content stream (e.g. JSON tweet) Add location annotations to JSON content Send annotated JSON content to aggregator and situation assessment picture building Map reduce type architecture for distributed geoparsing
  • 11. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geoparsing and geosemantic annotation 10 Exploiting linked open geospatial data OSM location matches  OSM ID set  linkedgeodata.org URI’s linkedgeodata.org URI  linked dbpedia.org URI  Semantic context Semantic context  Reports for decision support visualization GeoServer WMS visualization
  • 12. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium New York Hurricane Sandy 2012 Storm Surge Flooding Middleton, S. Middleton, L. Modafferi, S. (2014) Real-time Crisis Mapping of Natural Disasters using Social Media. IEEE Intelligent Systems, 02 Jan. 2014. IEEE computer Society Digital Library. IEEE Computer Society 11 Flooded Roads Flooded Areas Flooded Buildings
  • 13. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geosemantic knowledge model for trust and credibility analysis 12 Evidential approach to situation assessment and trust modelling Geospatial knowledge representation In real-time as situation develops incrementally build knowledge-base Assert JSON location annotations as OWL individuals + OSM tag metadata as OWL properties Subclass GeoSPARQL geo:Feature to encode geometry Results include linkedgeodata.org URI’s for OSM locations so we can later add Dbpedia linked data entries for end user reports
  • 14. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geosemantic knowledge model for trust and credibility analysis 13 Inference model for trust and credibility analysis Using image features and location OSM features Instagram (text)  Geoparse  owl_loc + owl_feature_props Instagram (image)  Image classifier  owl_feature_props features(text) == features(image)  loc_credibility++ Using location geography Tweet (text)  Geoparse  owl_loc + GeoSPARQL_geom Instagram (text)  Geoparse  owl_loc + GeoSPARQL_geom owl_loc ST_Dwithin( 500m ) owl_loc  loc credibility++
  • 15. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geosemantic knowledge model for trust and credibility analysis 14 Inference model for trust and credibility analysis Using trusted lists of users Tweet (text)  Geoparse  owl_loc + owl_author_prop Trusted list (end user)  owl_trusted_user owl_loc_author IN [owl_trusted_user]  trusted++ (Geo)SPARQL queries to filter relevant / credible / trusted results SPARQL to classify owl_loc individuals that match known facts about the breaking news story GeoSPARQL to classify owl_loc individuals based on OpenGIS geometry [nearby, connected_to, within_admin_area]
  • 16. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Geosemantic knowledge model for trust and credibility analysis 15 Experiences so far Storm supports scalable incremental processing really well Spatial filtering is key when dealing with Planet OSM database owl:restriction’s allows incremental inference via 'class-individual mirror' inference pattern e.g. evidence arrives, end user axioms asserted such as trusted users Open questions regarding geosemantic inference Which triple store is best for GeoSPARQL? OWLIM-SE? We have access to geometry in PostGIS and OWLIM-SE. Trade off between efficiency of SQL and inference of GeoSPARQL?
  • 17. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Conclusions 16 Future work 1st year prototype storm deployment due Nov 2014 4 social media sources Geoparsing locations in parallel on a storm cluster Real-time situation assessment map visualization Incremental geosemantic reasoning Scalability testing – cluster deployment testing on location data from several complete cities Scientific evaluation - we will gather ground truth from journalists in a real news room for several target breaking news stories in 2015
  • 18. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Many thanks for your attention! 17 Any questions? Stuart E. Middleton University of Southampton IT Innovation Centre email: sem@it-innovation.soton.ac.uk web: www.it-innovation.soton.ac.uk twitter:@stuart_e_middle Any questions?
  • 19. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Project partners & where to find us 18 The SAM project ”The research leading to these results has received funding from the European Union Seventh Framework Programme under grant agreement #610928. The positions expressed are those of the authors and do not necessarily reflect the views of the European Commission”
  • 20. REVEAL Project: Co-funded by the EU FP7 Programme Nr.: 610928 www.revealproject.eu © 2014 REVEAL consortium Axillary slide: Class-individual mirror inference pattern 19 <itinno:River> rdfs:subClassOf <geo:Feature> <ns:river1> rdf:type <itinno:River> <ns:river1> itinno:name "River Itchen" <ns:river1> geo:hasGeometry <ns:geom4> <ns:geom4> rdf:type <geo:Geometry> <ns:geom4> geo:asWKT "POLYGON((...))"^^<http://www.opengis.net/def/sf/wktLiteral> <itinno:NearbyRiverItchen> owl:equivalentClass [ a owl:Restriction; owl:onProperty itinno:nearby; owl:hasValue <river1>] SELECT ?loc WHERE { ?loc rdf:type <geo:Feature> . ?loc rdf:type <itinno:NearbyRiverItchen> . ?loc geo:hasGeometry ?g . ?g geo:asWKT ?wkt . FILTER( geof:sfContains( ?wkt, "POLYGON((...))"^^<http://www.opengis.net/def/sf/wktLiteral> ) ) }