sbir topic a04-105: an ontologically-based data fusion model
DESCRIPTION
SBIR Topic A04-105: An Ontologically-Based Data Fusion Model. Chris Matheus & Mitch Kokar Versatile Information Systems, Inc. cmatheus, [email protected] www.vistology.com. Outline. JDL Model Motivation, objectives, requirements Meta-modeling framework IFRM – top level - PowerPoint PPT PresentationTRANSCRIPT
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SBIR Topic A04-105: An Ontologically-Based Data Fusion Model
Chris Matheus & Mitch Kokar
Versatile Information Systems, Inc.
cmatheus, [email protected]
www.vistology.com
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Outline
• JDL Model• Motivation, objectives, requirements• Meta-modeling framework• IFRM – top level• IFRM – first step refinements• Ontologies and fusion• How many ontologies can be used?• Commercialization – an idea• Tasks• Backup slides
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SOURCE PRE - PROCESSING
LEVEL ONE PROCESSING
OBJECT REFINEMENT
LEVEL TWO PROCESSING
SITUATION REFINEMENT
LEVEL THREE PROCESSING
THREAT
REFINEMENT
LEVEL FOUR PROCESSING
PROCESS REFINEMENT
DATA FUSION DOMAIN
DATA BASE MANAGEMENT SYSTEM
FUSION DATABASE
SUPPORT DATABASE
SOURCES
LOCALDISTRIBUTEDNATIONAL
INTEL
EW
SONAR
RADAR . . .
DATA BASES
HUMAN COMPUTER
INTERACTION
USERS
WA - SOT assessment for Multi - source/sensor capability:
Mature / AvailableLab Demos / Not FieldedResearch Required
* From JDL/DFG Data Fusion Model
JDL Model
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Fusion: JDL Model
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Motivation
• JDL has seen a lot of attention
• But mainly Level 1 has been tested
• Recent emphasis on higher-level fusion made JDL insufficient
• Moreover, JDL has been misinterpreted as a data flow model
• Still needs a process model– Connected by “bus” – too flexible– Layered – too restrictive
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Reference Model - Impacts
• Improve development efficiency• Enable application portability and
scalability• Ease application adaptability• Improve system interoperability (NCW!)• Improve user productivity and portability• Promote vendor independence• Improve security• Reduce life-cycle cost
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Phase I Objectives
• Analyze reference models, identify useful features
• Propose adding process model to JDL• Formalize proposed model• Propose model evaluation approach and tools• Select application for validation in Phase II• Disseminate findings (papers, presentations)• Prepare an RFP for the OMG
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Model Requirements
• Be descriptive – serve the fusion community• Capture data, functions, processes• Represent fusion processes – allow comparison of
systems before they are built• Capture metrics of performance• Ontologically based – formal, computer processable
semantics• Formal specification of the model itself• Have a place for capturing human-in-the-loop and
user models• Have associated software tools• Compatibility with current models (as much as
possible, but not more)
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Meta-Modeling Framework (MMF)
MetaModel
Model
Objects Objects of interest in the domain (instances)
Classes of objects and relations among classes(Need modeling elements to define models)
Definition of modeling elements
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MMF – Software Engineering
MetaModel
Model
Objects new Employee(“John”)new Employer(“IBM”)
Class, Association, …UML
ClassDiagrams
JavaObjects
Employee:Class, employedBy:Association
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MMF – Semantic Web
MetaModel
Model
Objects <Employee John /><Employer IBM />
Class, Property, …OWL
Ontology
Annotation(markup)
<Class Employee /><Property employedBy />
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MMF – Information Fusion
MetaModel
Model
Objects track51:Track1, tankA1:TankB,
IFRM Terms (Class, Property, Track,Object, Situation)
IFRM
Model ofFusion System
Fusion System(run time)
System model (Track1:Track, O1:Object,TankB:Tank)
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Three Views
Process
Function
0..*
1
Performs
Product
0..*
1
IsResponsibleFor
2..*0..*Uses
0..*0..*Produces
1
0..*
1
0..*0..*
0..*
2..*
0..*
+Input
+Output
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Refinement: Product
Product
Signal
Individual Object
Track
Situation Object
Object Act ion Effect
This is just a first refinement step, not even complete …
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OODA
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OODA in UML
Process
Decision0..*0..*
Orientation
0..*0..*
+basis
Observation
0..*0..*
+theObservation
+decisionFeedback
+guidanceAction
0..*0..*
+theAction
+actionFeedback
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Refinement: Function(just an example)
Function
Output
getInput()
SubObject Assessment
Object Assessment
Situation Assessment
Impact Assessment
Orientation
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• ontology 1. the branch of metaphysics dealing with the nature of being, reality or ultimate substance (cf. phenomenology) 2. particular theory about being or reality
• phenomenology 1. the philosophical study of phenomena, as distinguished from ontology 2. the branch of a science that classifies and describes its phenomena without any attempt at metaphysical explanation
• metaphysics 1. the branch of philosophy that deals with first principles and seeks to explain the nature of being or reality (ontology); it is closely associated with the study of nature of knowledge (epistemology)
Ontology (Webster)
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• An explicit specification of a conceptualization: the objects, concepts, and other entities that are assumed to exist in some area of interest and the relationships that hold among them (Genesereth & Nilsson, 1997)
• Definitions associate the names of entities in the universe of discourse (e.g., classes, relations, functions, or other objects) with human-readable text describing what the names mean, and formal axioms that constrain the interpretation and well-formed use of these terms. A statement of a logical theory. (Gruber)
• An agent commits to an ontology if its observable actions are consistent with the definitions in the ontology (knowledge level).
• A common ontology defines the vocabulary with which queries and assertions are exchanged among agents.
Ontology (cont.)
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Ontologies and IFRM
• IFRM is at the same level as UML and OWL (from the linguistic point of view)
• IFRM is a domain-specific (information fusion) modeling language– Ontology defines a conceptualization, a
vocabulary …
• Thus IFRM is an ontology, provided it is specified explicitly in a formal language (formal axioms)
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Ontologies and Fusion System
MetaModel
Model
Objects Annotations
IFRM = Ontology of FusionIFRM
Model ofFusion System
Fusion System(run time)
Specific ontology
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Commercialization Idea
• Achieve acceptance by the fusion community• Achieve acceptance by the Government• Request for Proposals (RFP) for standards -
the OMG• Work with OMG towards standard (IFRM)• Promote the standard• Build supporting tools• Result: Interoperability of various fusion
systems!
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Tasks
Task 1 2 3 4 5 6 7 8 9
A. Analyze other models
B. Refine the model
C. Formalize top-level model
D. Develop evaluation methodology
E. Propose software tools
F. Identify evaluation scenarios
G. Prepare RFP to OMG
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Backup Slides
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Ontology Languages
• Web Ontology Language (OWL)– Lite– DL (Description Logics)– Full
• OWL+SWRL (Semantic Web Rule Language)
• RuleML
• First Order Predicate Calculus (FOPL)
• Higher Order Logics (HOL)
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OWL & SWRL
XML
RDF
RDFS
OWL
SWRL
Extensible Markup Language
Resource Description Framework
RDF Schema
Web Ontology Language
Sem. Web Rule Language
Note: The layering of OWL on top of RDFS is not strict.
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How many ontologies?
• Net Centric Warfare (NCW) requires full interoperability and thus communication
• An agent commits to an ontology if its observable actions are consistent with the definitions in the ontology (knowledge level).
• Two agents must commit to the same ontology in order to communicate
• What if there are N agents?– One common ontology? Seems impossible!– N2 ontologies? Unmanageable!– Ontology mapping? Work in progress.– Core ontology + extensions? Compromise.
• Somewhat similar idea to NATO’s Generic Hub (GH5) and C2 Information Exchange Data Model (C2IEDM)
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C2IEDM Core
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GH 5 Core
CANDIDATE-TARGET-LIST
CAPABILITY
RULE-OF-ENGAGEMENT
REPORTING-DATA
LOCATIONOBJECT-TYPE OBJECT-ITEM
CONTEXT
ACTION
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GH5 Core
• A neat idea– Common core, extendable– Relatively rigorous– Substantial amount of knowledge– XML Schema available
• Not an ontology– Not formal (no formal semantics)– Thus cannot be processed by logical tools– Not quite compatible with MMF (mixes Object and
Model levels)– But looks like a good start towards an ontology
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VIS SAW Core Ontology
SBIR Phase II, AFRL/IF Rome, Mike Hinman, John Salerno
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Battlefield Ontology
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What is “extension”?
• Add classes– E.g., Battalion is a Unit
• Add properties (relations)– E.g., Platoon is part-of Company
• Add constraints– E.g., Soldier can be part of only one
Platoon
• But the result must be an ontology that is consistent
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Consistency
con•sis•ten•cy
agreement with what has already been done or expressed;conformity with previous practice
[Webster’s]
In logic: from P and not(P) can derive anything
Inconsistency is a dangerous thing for autonomous agents!
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Inconsistency: Example
• Battlefield Ontology happens to be consistent• Suppose we have
– Constraint: Unit must have at least 8 Soldiers
• Suppose we then extend it by adding:– Class: Group (sub-class of Unit)– Constraint: Group has 3 Soldiers
• Inconsistency!• Easy to generate inconsistencies while developing
ontologies• ConsVISor to the rescue: http://www.vistology.com
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Ontology Mapping
DB1 DBd KB1 KBkSsS1
Tt Oo
T1 O1
AD1 ADd AK1 AKk
ATt
AO1
AS1 ASs
AT1
AOo
GUI
Agents: commit to ontologies; negotiate mapping; use templates
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Ontology Mapping (cont.)
• Need to map:– Classes to Classes– Properties to Properties– Objects to Objects– Constraint mapping implicit
• May result in inconsistency!
• ConsVISor to the rescue: http://www.vistology.com
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Why Use Ontologies?1. Represent theories of potential objects and relations as ontologies (OWL)
2. Represent collected data as annotations in terms of ontology (OWL)
3. Formulate any queries about situations in OQL (OWL Query Language)
4. Use a general purpose OWL reasoner to answer queries
5. Use the trace of the reasoner to give an explanation to user
6. Multiple ontologies may need to be combined into one (fusion)
7. Data Association and Fusion
1. association of objects with ontologies/annotations
2. relations among objects within ontologies/annotations
3. combining ontologies/annotations using colimit of category theory
Flexibility: Can use the same reasoners on any ontologies and annotations!
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Use Case: Ontology-Based Fusion
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Use Case: Fusion System Development