Data Fusion based on ontology model for Common Operational Picture using OpenMap and Jena semantic f

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Data Fusion based on ontology model for Common
Operational Picture using OpenMap and Jena
semantic framework

• Capt. Mariusz Chmielewski
• mchmielewski_at_wat.edu.pl
• Computer Science Department,
• Cybernetics Faculty ,
• Military University of Technology

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Presentation plan

• Definition of modeling domain
• NEC, Situation Awareness, Information
  Superiority, Common Operational Picture
• Ontologies semantic models
• Knowledge representation
• Formal model of ontology
• Languages of semantic networks
• Application of ontologies for COP
• C4I systems migration strategies
• Method for model transformation
• Environment architecture
• Toolkit presentation
• Future Development

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Network Enabled Capabilities - Summary

• Network Enabled Capabilities - military doctrine
  or theory of war
• Based on information advantage, made available by
  the information technology, into a competitive
  combat advantage through the efficient network
  mechanisms delivered for geographically dispersed
  forces.
• Main statements
• Efficient networked mechanisms (distinctly
  improve information flow and information sharing
  abilities
• Information sharing enhances the quality of
  transferred information and in result situational
  awareness of the battlespace
• Shared situational awareness enables
  collaboration between sensors, actors and command
  centers improving synchronization, and reduces
  the communication delays which in result speed
  up decision process and increase mission
  effectiveness.

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COP, SAW in definitions

• Common Operational Picture is a single
  identical display of relevant information shared
  by more than one command. A common operational
  picture facilitates collaborative planning and
  assists all echelons to achieve situational
  awareness

Situation awareness (SAW) can be understand as a
perception of environmental elements within a
volume of time and space, the comprehension of
their meaning, and the projection of their status
in the near future. SAW bounds perception and
environment critical to decision-makers in
complex, dynamic processes, in this case -
military command and control.
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COP services

• COP can be defined as a service or a set of
  services providing
• Collection of recognized pictures
• Data fusion and correlation of recognized
  pictures
• filtering technology for commander as also if
  available interoperability link to source C4I
  system
• COP supports current shared operation picture
  containing elements from
• RAP (Recognised Air Picture),
• RMP (Recognised Maritime Picture),
• RGP (Recognised Ground Picture),
• RLP (Recognised Logistics Picture)
• Intelligence systems
• Decision support procedures

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Semantic Models, Ontologies

• Origin of technology - Next stage of the Internet
  evolution, Semantic Web.
• Semantic description can improve the way
  information is presented.
• Semantic data representation - based on graph
  model - RDF concept of triples representing
  resources and data describing them.
• An ontology is used as a tool for describing and
  representing selected knowledge branch that is
  medicine, finances, battlefield etc.

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Model of ontology
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Model of semantic network

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Languages of semantic networks

• dedicated languages
• RDF, RDF-S, SHOE, DAMLOIL, OWL (Ontology Web
  Language)
• share the same theoretical framework extended
  towards Description Logics to provide knowledge
  representation and reasoning mechanisms.
• In terms of the expressivity, these languages can
  be arranged in an order RDF, RDF-S, SHOE,
  DAMLOIL and OWL.
• OWL provides sublanguages
• OWL Lite - expressiveness is limited (restricted
  primitives list), but in this case the efficiency
  of reasoning is preferable,
• OWL DL (Description Logics) - is as expressive as
  possible on the premise of preserving
  completeness and decidability of reasoning
• OWL Full - is required for modeling domains using
  full spectrum expressiveness with no
  computational guarantees of reasoning.

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Modeling Battlespace Ontology

• The core element of the designed tool is usage of
  an ontology and therefore a semantic model
  representing the battlespace (UBOM) Unified
  Battlespace Ontology Model.
• Development based on ontology modeling
  metodologies, contains
• Definition of researched domain and boundaries of
  modeling
• Existing ontology (domain models) overview and
  decision of application
• Definitions of elementary abstractions within the
  domain creation of important concept list
• Concept taxonomy modeling - class definition and
  their hierarchy
• Class property modeling identifying properties
  (slots) for classes (definition domain and range
  definition)
• Property restriction definition object type or
  datatype specification
• Identification of instances and their
  classification within the class taxonomy

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Elements of UBOM

• Ontology development for the COP enabled tool
  required detailed C4I system datasources
• aspect of visualization mechanism
• GIS data standard used by the system.
• Unified Battlespace Ontology Model (UBOM) has
  been divided into two parts
• MIP JC3 model based ontology describing wide
  range of military operations and the whole domain
  of military units and equipment
• Decision support ontology containing concepts
  of decision, variant and the rest of decision
  process realized on the battlefield

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Overcoming ontology differences

• Two kinds of ontology mediation
• ontology mapping
• Correspondences are stored separately from the
  ontologies
• Mappings are not part of the ontologies
  themselves.
• Correspondences can be used for, querying
  heterogeneous knowledge bases using a common
  interface or transforming data between different
  representations.
• ontology merging
• Produces a new ontology which is the union of the
  source ontologies
• Merged ontology encapsulates all the knowledge
  from the original sources
• Described process must ensure that all
  correspondences and differences between the
  ontologies are reflected in the merged ontology.

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Overcoming ontology diferences

• Stages of semantic mapping
• Importing the content of the ontologies to chosen
  ontology language
• Normalization of defined vocabularies through
  elimination of lexical and syntactical
  differences
• Similarity evaluation of ontology entities using
  defined set of parameters
• Ontology quantity analysis - predefined sets of
  indicators
• Establishing correspondences between similar
  entities (concept thesaurus), in the form of
  semantic bridges linking similar concepts
• Utilizing developed mappings for instance
  transformation
• Revision of prepared mappings for improvements

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Datasources providing combat scenario
Legacy Polish Armed Forces C4I systems Szafran,
Dunaj, Podbial, Leba Simuators Scenario Zlocien
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Construction of battlespace picture

• GIS Data Sources
• Layers
• Semantic model
• Filters
• Decision support procedure

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Components of developed solution

• Distributed GIS environment
• Ontology processing mechanizms
• Data migration mechanisms

Integration -gt OSGi framework based on Eclipse
Equinox implementation
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Components of developed solution

• OpenMap - open GIS framework providing core
  mechanisms for COP visualization and semantic
  queries
• NASA WorldWind 3d visualization toolkit
  providing a Earth 3D model with a satellite high
  quality pictures cover and detailed Earth terrain
  model
• JENA Semantic Framework framework dedicated to
  process semantic models stored in RDF, RDFS, DAML
  and OWL, supporting SPARQL query language, SWRL
  rules language, inference mechanisms and graph
  persistence
• JESS Rules rule based inference engine which
  uses an enhanced version of the Rete algorithm to
  process rules. Tool provides also a extended
  scripting language for Java allowing to build
  applications using imperative language.
• Shrimp Visualization Toolkit a innovative
  method of visualization large scale data extended
  towards ontology models and implemented as a
  Protégé plugin Jambalaya.

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Distributed GIS Environment
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Ontology processing

• Protege JENA Semantic Framework
• process semantic models stored in RDF, RDFS, DAML
  and OWL
• Automated modeling
• supporting SPARQL query language,
• SWRL implementation - rule language for semantic
  data
• Inference mechanisms
• Graph persistence
• Graph visualisations

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Visualisation Enviroments NASA WorldWind
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Visualisation Environments OpenMap
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Ontology Tool for COP
Integrated COP
Ontology Processing
Overview compont
GIS Toolbox, Coordinates calculator
GIS Layers Decision support procedures
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Future development

• extending the presentation layer with 3D GIS
  projection of terrain based on JOGL and Java 3D
  API
• remote reconnaissance tool allowing better
  understanding of battlespace and current combat
  scenario
• development directions are mobile solutions
  providing CTP or COP solution
• SOA based environment and specialized software
  platform (PDA, Smartphone) provide decision
  support tools on lower level command

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Thank You

• Author
• Capt. Mariusz Chmielewski
• email mchmielewski_at_wat.edu.pl
• Computer Science Department,
• Cybernetics Faculty ,
• Military University of Technology

ACKNOWLEDGEMENTS This work was partially
supported by grant Research Project No
PBZ-MNiSW-DBO-02/I/2007.