Ontology-based Data Access for Maritime Security

Ontology-based Data Access

for Maritime Security

Stefan Brüggemann1_{, Konstantina Bereta}2_{, Guohui Xiao}3_{, Manolis Koubarakis}2 1 _{Airbus Defence & Space, Germany}

2 _{University of Athens, Greece}

3 _{Free University of Bozen-Bolzano, Italy}

Maritime Concept

2/3 of cargo worldwide transported overseas

Maritime Concept

2/3 of cargo worldwide transported overseas

Offshore windparks -> need to be protected

Maritime Concept

2/3 of cargo worldwide transported overseas

Offshore windparks -> need to be protected

Crimes over seas, natural disasters

EMSEC project

• Increasing the maritime situation awareness

• Data fusion. Integration of Earth Observation (EO) data with

conventional data streams and data from multiple other sources

• Target: to initiate a coordinated service network to provide all the national users (BOS – security agencies and organizations) with integrated maritime services in Near-Real Time (NRT)

Goals and Challenges

Goals :

• Tracking of vessel movements

• Detection of abnormal vessel behaviours

Challenges:

• Heterogeneous sources for vessel data: dynamic and static

• Real-time acquisition of vessel positions (dynamic data): 1000 or more vessels send their position frequently.

Data sources

Movement and pattern identification

RMSAS: Real-time Maritime Situation

Awareness System

Data Integration

RMSAS: Real-time Maritime Situation

Awareness System

RMSAS: Real-time Maritime Situation

Awareness System

RMSAS: Real-time Maritime Situation

Awareness System

RMSAS: Real-time Maritime Situation

Awareness System

RMSAS: Real-time Maritime Situation

Awareness System

RMSAS: Real-time Maritime Situation

Awareness System

Semantic Web technology solution

Semantic Web technology solution

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

Ontologies

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

• Representing and querying geospatial information

Ontologies

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

• Representing and querying geospatial information

Ontologies

OBDA

GeoSPARQL Ontop-spatial

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

• Representing and querying geospatial information • Enrich information with linked open data

Ontologies

OBDA

GeoSPARQL Ontop-spatial

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

• Representing and querying geospatial information • Enrich information with linked open data

Ontologies

OBDA

GeoSPARQL Ontop-spatial

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

• Representing and querying geospatial information • Enrich information with linked open data

Ontologies

OBDA

GeoSPARQL Ontop-spatial

Semantic Web technology solution

• Heterogeneous Data: Need for harmonization, integration • Avoid the materialization of frequently updated data

• Representing and querying geospatial information • Enrich information with linked open data

Ontologies

OBDA

GeoSPARQL Ontop-spatial

RMSAS Semantic

Analysis Component

The Ontop System

• OBDA system: On-the-fly SPARQL-to-SQL translation on top of relational databases

• Enables RDFS/OWL QL reasoning

• Developed by the University of Bolzano [SWJ ‘16, JWS ‘15]

Ontop-spatial extension:

• Extension of Ontop with GeoSPARQL support

• Enables on-the-fly GeoSPARQL-to-SQL translation

• Browser and visualizer of linked geospatial data

• Connects to (Geo)SPARQL endpoints and projects the geospatial results of queries on the map

• Supports also widely-used standard geospatial formats (e.g., KML, Shapefiles, (Geo)JSON, GeoTIFF).

• Support for Statistics

• Enables users to correlate geospatial information coming from auxiliary files with linked geospatial data

•

Retrieving the locations of vessels

SELECT DISTINCT ?x ?z ?g ?timestamp WHERE { ?x rdf:type :Vessel. ?x :hasName "Vesselname”. ?x :hasLocation ?z. ?z :hasDateTime ?timestamp . ?z geos:asWKT ?g. }

Areas intersecting ports

SELECT DISTINCT ?lu ?geo WHERE { ?x osm:landUse lgd:port . ?x geo:asWKT ?geo . ?x1 geo:asWKT ?geo1 . ?x1 osm:landUse ?lu . FILTER (geof:sfIntersects(?geo,?geo1))} GeoSPARQL

Retrieve locations and info about vessels

SELECT * WHERE {

SERVICE <http://www.rmsas.de/openrdf-sesame/PositionStore> {

?vessel rdf:type :Vessel . ?vessel :hasLocation ?location .

?vessel :hasName "388328333". ?location :hasGeometry ?geometry . ?geometry geos:asWKT ?wkt .

OPTIONAL {

SERVICE <http://www.rmsas.de/openrdf-sesame/ObjectStore> {

Lessons learned

• Using SW technologies and applications improved data integration • Conceptualized view improved operational logic understanding

• Satisfactory performance

• Feedback to SW tools: technical, usability issues • Learning curve

Conclusions and Future Work

Thank you!

Questions?

Related Links:

EMSec project: http://www.emaritime.de/projects/emsec/ Ontop Project: http://ontop.inf.unibz.it/

Ontop-spatial extension: https://github.com/ConstantB/ontop-spatial Sextant: http://sextant.di.uoa.gr/