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On the Use of the Web Ontology Language (OWL) for C-‐BML Standards Development
Kevin Gupton [email protected]
Modeling & Simula8on Informa8on Management Branch Signal and Informa8on Sciences Laboratory Applied Research Laboratories The University of Texas at Aus8n
APPLIED RESEARCH LABORATORIES
THE UNIVERSITY OF TEXAS AT AUSTIN 2
Development Challenges (1)
• Mul8ple stakeholders and communi8es
• Diverse requirements from different communi8es – Enough overlap to jus8fy working together. – Enough conflict and contradic8on in our requirements to cause scope
problems.
• Diverse scope – Opera8onal, tac8cal, and system Use Cases
• Diverse expecta8ons for C-‐BML specificity – General framework, or implementable solu8on?
More generic: supports more users, not a real implementa5on
More specific: ready-‐to-‐use solu5on, serves fewer users
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Development Challenges (2) Need a C-‐BML architecture that provides frameworks for suppor8ng
– Diverse requirements – Variable degrees of specificity – Rules, constraints, and nuances of communi8es, without forcing
one stakeholder’s constraints on others. – The mul8ple standards, systems and architectures of each
stakeholder. – Mul8ple overlapping, conflic8ng, or dis8nct domain models.
– Mul8ple layers of community and applica8on extensions.
The Web Ontology Language (OWL) and other semanFc technologies have essenFal features for managing these challenges.
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Founding Principles • C-‐BML PDG guidance
– “That the phase 1 specifica5on includes a logical mapping of C-‐BML to the JC3IEDM Logical Data Model, as part of the norma5ve specifica5on.”
• Engineering best-‐prac8ces: – Model Based Data Engineering (MBDE) and Model Driven Architecture (MDA)
– Strictly derive physical data formats (such as grammars and XML schemas) from common data models.
– By defini5on, formal grammars are purely syntac5c, and meaning must be provided by an interpreta5on with respect to a data models and logical systems.
DATA
Model
Grammar / Language
grammars are bound to a model
constrains format
gets meaning from
DATA DATA
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• Mul8ple grammars, XML schemas, or tac8cal message formats can exist across an opera8onal environment, all derived from a common data model.
• Without a common data model, we cannot ensure that any data formats will be interpreted consistently.
MSDL XML OIEG
C2 Core C2LG
PracFcal Arguments
Model
Tac8cal message sets C-‐BML
Grammar
JC3IEDM XML
GFMIEDM Grammars:
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ONTOLOGY-‐DRIVEN DEVELOPMENT
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Web Ontology Language (OWL) Just enough to get by… • Individuals are instances.
• Classes and subclasses are sets and subsets of individuals.
• ObjectProper8es relate Individuals.
• DataProper8es define a_ributes for Individuals.
What’s important here… • URIs are the iden8fiers.
– URIs for real things • Bridges, houses, event, people,
ci8es, ac8ons
– Globally unique across the web. – Means we can reference and
describe any “thing” anywhere.
• Impor8ng and extending any data set or data model is simple and dynamic. – Integra8on of data models can
occur dynamically and distributed.
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Managing Distributed Domain Models MIP JC3IEDM
or other C2 ontology
SISO MSDL (as a model)
SISO C-‐BML model
NATO OPORD extensions USMC extensions Extensions for Autonomous Agents
Organisa8on
Unit
Resolu8on
TaskerWho
Who
Order
OPORD FRAGO WARNO OPORD Agent Order
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Managing Distributed Domain Models MIP JC3IEDM
or other C2 ontology
SISO MSDL (as a model)
SISO C-‐BML model
NATO OPORD extensions USMC extensions Extensions for Autonomous Agents
Organisa8on
Unit
Resolu8on
Import and extend…
By referencing URIs.
TaskerWho
Who
Order
OPORD FRAGO WARNO OPORD Agent Order
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View from C-‐BML today
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Develop Models as Modular Components
• Par88on ontologies across workspaces, based on: – separa8on of concern – scope / level of specificity – need to know – releasability – product maturity
– classifica8on • Standardize the common & reusable • Adopt a framework for distributed
model extension
• Separate the private, specialized, & experimental
MIP, SISO, IEEE, seman8c web
Coali8on
DoD Metadata Registry
Proprietary
Private
Experimental
Academia Commercial
ONTOLOGIES:
APPLICATIONS:
Classified
Applica8on-‐specific
core
common
custom
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Defining Conformant Grammars
MIP JC3IEDM
SISO C-‐BML model
NATO OPORD extensions
USMC extensions
C-‐BML XML
MODEL MESSAGES SCHEMA JC3IEDM WS-‐OO XML
JC3IEDM RDBMS XML
C2LG extensions
OIEM extensions
SISO MSDL (as a model)
MSDL XML
C2LG
OIEG
NATO OPORD syntax
USMC syntax
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SUPPORTING OTHER DOMAIN MODELS: DECOUPLING FROM JC3IEDM
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Tasking within a Domain There is an interest in loosening the dependency to
JC3IEDM. – Not wan8ng to discard JC3IEDM.
– But want to enable users to use other domain models
– Such as… • Crisis management • C2 Core • Na8on or service-‐specific domain model • Logis8cs and Transporta8on (e.g., TPFDD)
SoluFon: sFll more modularity…
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MIP JC3IEDM
Current Perceived Coupling
SISO C-‐BML model Organisa8on
Unit
TaskerWho
Who
Order
Tight coupling; direct reference
Crisis Management Domain Model
Crisis Manager
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Pa^ern for Ontology Decoupling
MIP JC3IEDM SISO C-‐BML model
Organisa8on
Unit TaskerWho
Who
Order
Crisis Management Domain Model
JC3IEDM/C-‐BML binding ontology
Unit TaskerWho
imports
Coupling happens here, in another ontology module
Crisis Manager
Crisis Mgmt/C-‐BML binding ontology
Crisis Manager TaskerWho
imports
Other domain models may be used instead
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Work Items: Things to be Done (1)
• C-‐BML logical data model – Ensure C-‐BML Phase 1 is properly represented in a data model.
– Create OWL representa8on of model.
• Capture C-‐BML / JC3IEDM alignment – Create OWL representa8on of JC3IEDM. – Define alignment & integra8on of C-‐BML with JC3IEDM using OWL
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Work Items: Things to be Done (2)
• C-‐BML / MSDL alignment – Derive data model for MSDL – Create OWL representa8on of MSDL
– Define alignment of JC3IEDM to MSDL model – Define alignment of C-‐BML model to MSDL model
• Support mul8ple domain models – Restructure C-‐BML to be “composable” with JC3IEDM, not dependent on JC3IEDM.
– Define other domain models in OWL (e.g., crisis management)
– Define binding of C-‐BML with other domain models
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Work Items: Things to be Done (3)
• Guidelines for binding (“gluing”) expressions and grammars to the C-‐BML ontology. – Guidance for genera8ng and parsing expressions unambiguously.
– Define specific bindings for C2LG, OIEG, MSDL tasking extensions, as well as official C-‐BML grammar.
• Need a C-‐BML Architecture for handling stakeholders’ requirements…
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Proposed Architecture for C-‐BML SpecificaFon
C-‐BML specifica8on P3: C-‐BML ontology
imported ontologies
JC3IEDM ontology
Domain ontology:
crisis management ontology
C-‐BML abstract expression guideline
C-‐BML grammar guideline
P1: C-‐BML vocabulary
P2: C-‐BML reference abstract expressions
P2: C-‐BML reference grammar
C-‐BML domain ontology guideline
C2LG abstract expressions
C2LG grammar OIEG abstract expressions
OIEG grammar
C-‐BML grammar transform guideline
Where do your requirements fit?
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SemanFc technologies can contribute in other ways, as needed…
• SPARQL query language standard has mechanism for defining abstract expressions.
• Mul8ple grammar standards exist for exchanging OWL data at run8me.
• Data fusion • Data integra8on • Machine reasoning
• Expert systems and tac8cal decision aids
• Data transla8on and media8on
• Truth / belief frames for data
• Suppor8ng dynamic problem spaces where models, metrics, and methods may change month to month: – irregular warfare – influence opera8ons
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SemanFc Web of Linked Data
203 Linked SemanCc Web Knowledge Bases
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SemanFc Web of Linked Data
203 Linked SemanCc Web Knowledge Bases
To succeed, development of C2, M&S, and C-‐BML ontologies must be a “social” ac5vity.
Like any data model, growing ontologies in the dark perpetuates gaps in understanding.
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On the Use of the Web Ontology Language (OWL) for C-‐BML Standards Development
Kevin Gupton [email protected]
Modeling & Simula8on Informa8on Management Branch Signal and Informa8on Sciences Laboratory Applied Research Laboratories The University of Texas at Aus8n
QuesFons?
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Miscellaneous challenges
• What are our domain ontologies? We need a C2 ontology. – JC3IEDM can be used to start construc8on of a basic upper C2 ontology.
• JC3IEDM is structured around rela8onal-‐database biases. Meaning, JC3IEDM is structured as a database, not as a conceptual data model. – A JC3IEDM-‐based ontology would require minor refactoring to follow good ontology design prac8ces.
• We must use requirements to steer our development – We can “ontologize” the C2 domain ad infinitum, so how do we know when we’ve modeled enough of it for C-‐BML?
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Standards and Tools
• URI • RDF • RDFS • OWL2 • OWL-‐S
• SPARQL • SWRL • GRDDL • SKOS • FOAF • VCARD
• Protégé
• TopBraid Composer
• NeOn Toolkit
• Altova Seman8cWorks • PoolParty
• Jena
• OpenRDF
• Sesame
• Mulgara • Virtuoso
• Pellet
• Hermit
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A TASKING ONTOLOGY
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Speech Acts: IllocuFonary Force
• Credited to J.L. Aus8n. How to do Things with Words, 1962. • Cited and central to C2 Lexical Grammar (C2LG).
• Already formalized for systems engineering in FIPA CA…
Act Meaning Example
LocuFon The u_erance; the message.
He said to me, “Shoot him!”
IllocuFon The inten8on or func8on of the u_erance / message.
He ordered me to shoot him.
PerlocuFon The performance of the act. I shot him.
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FIPA
• IEEE standard: – Founda8on of Intelligent Physical Agents (FIPA)
• FIPA Communica8ve Acts (CA) specifica8on
• FIPA Agent Communica8on Language (ACL) specifica8on
• Others…
• Two ways of using FIPA: – Consider FIPA as an example implementa8on target (relevant to SAFs and robots).
– Learn from theory, formalism, and ra8onale.
• Ontologies have already been built around FIPA…
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FIPA to COMMONT
• CommOnt -‐ “Communica8on Ontology” – Jesús Bermúdez, Alfredo Goñi, Arantza Illarramendi, and Simone San8ni. 2007. Is an
OWL ontology adequate for foreign sopware agents communica8on?. Applied Ontology 2, 3-‐4 (August 2007), 351-‐372.
• Combines FIPA CA and Knowledge Query Manipula8on Language (KQML) with an ontology.
