Open Net-Centric Interoperability Standards for Training and Testing

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Open Net
-
Centric Interoperability Standards for
Training and Testing




Metadata Working Group


July 13, 2010



Carl Rosengrant


Readiness and Training Policy, and
Programs

Office of the Deputy Under
Secretary of Defense (Readiness)


Carl.rosengrant@osd.mil


Office of the Deputy Under Secretary

Of Defense for Readiness


Outline


Introduction


What is ONISTT?


How is it being used?


Way forward

2

What is ONISTT?

1.

A framework for representing knowledge about:

(a)

Capabilities

required to execute military tasks in various operational
contexts (
e.g
., in Training Exercises, in Testing Events, or in real
combat operations)

(b)

Resources

-

Real systems that can be assigned to play the various
roles associated with executing those military tasks in the designated
operational context



and

2.

An automated means for reasoning about that knowledge

with the goal of

Enabling agile interoperability

3

ONISTT Concept in 1 Slide


“Lady Justice” is a symbolic metaphor for the
process of implementing “blind justice”


The scales provides a means of assessing (weighing) the
strength of the charges against the defendant versus the
strength of arguments in his defense


The blindfold symbolizes the objectivity of the assessment,
based only on the facts presented (not on the physical
appearances of the plaintiff & defendant)


ONISTT is technology providing a means for automating Lady
Justice


The issue being assessed is whether the capabilities available from a
specified pool of resources (
the supply
) can satisfy the capabilities
needed to perform a specified task (
the demand
)


The assessment function is performed by a general purpose application
agnostic
inference engine
(not by procedural logic tailored for a specific
domain)


The facts and logic (about
the supply and the demand
) are captured in
Knowledge Bases (KBs) via a machine understandable language

4

So…What can we do with an automated
Lady Justice?

Quite a bit, actually







The “matching supply to demand” paradigm is a
rather profound concept that pervades many
application domains…

5

So… What Can You Do With an Automated
Lady Justice? (Current Efforts)



Determining whether an improvised confederation of Live
-
Virtual/Constructive
(L
-
VC) training systems can work harmoniously together to perform a mission
(one that none were originally designed to support)




Improvisational L
-
VC Interoperability



Determining whether an improvised confederation of testing resources can work
harmoniously together to provide a complex test environment for a Net
-
centric
System
-
Under
-
Test




Analyzer for Net
-
centric System Confederations Project



Determining whether a candidate system design can satisfy its performance
specification




Technical Data Package Example



Deriving a
ruleset

for downgrading information to allow flow from a higher security
domain to a lower security domain


AF Research Lab (Rome NY) Task



Creating and compiling ontologies based on DIS/HLA/TENA/CTIA object models
and publishing that knowledge to a repository


JFCOM Joint
Composable

Object Model Initiative



NATO working group is using ONISTT assets to demonstrate the feasibility of
automating semantic interoperability in coalition operations


ONISTT NATO Initiative






6

ONISTT: Ontology Development and
Knowledge Capture Phase

2.
Develop ontologies to express


pertinent characteristics of
referents necessary for machine
reasoning about interoperability

Ontologies

ONISTT Concepts

3.
Populate Knowledge Bases


on the basis of ontologies and


information in referents

Task

Knowledge Bases


Tasks


Roles


Capabilities needed


Task constraints

Resource and Domain

Knowledge Bases


Resources


Capabilities


Domain knowledge

Version 10
-
31
-
08

1a.

Develop referents for


training/testing events,
tasks, and environments

Training/Testing

Event Referents

Tasks

Training/Testing

Environments

LVC

Systems

1b.

Develop referents for


LVC systems, capabilities


and quality metrics

Training/Testing

Infrastructures

Training/Testing

Resource Referents

General Domain

Concepts

DoD Domain

Concepts

7

Analyzer

Decision

3a.

Return


notification


of failed
verification.


Back to Step 1

2.

Analyzer/Synthesizer uses information in


Knowledge Bases to

a)
Assess given Confederation or

b) Generate possible Confederations

from Resource Pool





ONISTT: Analyzer/Synthesizer
Employment Phase

Task

Knowledge Bases

Resource

Knowledge Bases

1.

Training/Testing Planner uses


Knowledge Bases to

a)
Define Taskplans

b)
Propose candidate
Confederation(s)


(full or partial)

Configuration

Artifacts

Verified

Confederation(s)

3b.

Return verified
Confederation(s)


and Configuration
Artifacts

Version 11
-
01
-
08

Deployment

Knowledge Bases


Resource pools


Confederations


Taskplans


Role assignments


Task constraints

8

Referent and Ontology

Description Languages


Referents


Natural language


UML (Unified Modeling Language)


Ontologies/Knowledge bases (KBs)


OWL (Web Ontology Language)


SWRL (Semantic Web Rule Language)


Bridging between UML and OWL


ONISTT team developed OWL “profile” for UML per Object
Management Group (OMG) Ontology Definition Metamodel (ODM)


ONISTT team recommendations were adopted by the OMG as
improvements to the ODM specification


Sandpiper tool

9

ONISTT/ANSC Benefits


Facilitates composition of improvised confederations of agile
systems


Discovers and verifies resource compositions tailored to a given
purpose


Optimizes use of existing resources


Partially automating BOGSAT process
--
replaces ad hoc, trial & error
approach


Exercise planners get rapid, reusable access to accumulated
expert information and lessons learned


Avoid repeating costly mistakes


Repeat successes


Focuses spotlight on areas that are problematic for
interoperability


Target them for improvement or standardization



10

Outreach Accomplishments


International Semantic Web Conference (ISWC) 2009
peer
-
reviewed paper


“Reasoning about Resources and Hierarchical Tasks Using OWL
and SWRL”


Winter Simulation Conference (WSC) 2009 invited paper


“Ontologies and Tools for Analyzing and Synthesizing LVC
Confederations”


Expanded version for Journal of Simulation (forthcoming)


IEEE Policy 2010 peer
-
reviewed paper


“Policy
-
Based Data Downgrading: Toward A Semantic Framework
and Automated Tools to Balance Need
-
To
-
Protect and Need
-
To
-
Share Policies”


www.onistt.org

Website (Send e
-
mail to Mr. Rosengrant
for access)

11

Way Forward


Although demos conducted to date have shown the potential
value of this technology, there remains considerable
development to be accomplished in order to “
operationalize

it”



Widespread deployment of commercial applications in
Semantic Web technology are facing many of the same
challenges, accelerating work in the area


We anticipate benefiting from these developments



We are seeking to collaborate with other organizations
who are working in
ontologies
, in order to leverage work
that might be otherwise have to be duplicated!

12

Questions?

13

Backup

14

Knowledge Capture Phase

Analyzer/Synthesizer architecture

ONISTT/ANSC Benefits


Flexible and reusable definition of test events and test
objectives


Allow for subtasks nested to arbitrary depth


Ensure complete coverage of test objectives by test events


Automatically check for adequate coverage of test value sets
(values of critical controlled variables)


Automated synthesis of a completed test plan


Generate valid refinements of given, partial plan


Automatically identify combinations of T&E resources best suited to
attain objectives


Synthesis problem is more difficult than analyzing a fully specified
test plan


Domain ontologies

Spatial reference frame, Entity, Quantity, Sensors,

Time, Terrain, Networks, Comm architecture (Link
-
16,

USMTF, TENA, DIS, OTH
-
Gold, VMF, IBS, Link
-
11,

voice)…

Capability ontologies

Engagement, Sensing, Countermeasure,

Communication, Appearance, Motion,

Terrain…

Task ontologies

Engagement, Sensing, Countermeasure,

Communication, Appearance, Motion,

Terrain…

Resource ontologies

JSAF, JIMM, JIMES, C3Driver, JSTARS, VSTARS,

EA6B_WSSL, F/A
-
18 AWL, E2C ESTEL,Pt Mugu,

Pax River, Ft Huachuca,Eglin, Edwards, China Lake,

White Sands, InterTEC/JMETC comm infrastructure...




Task plan ontologies

JSAF Tomahawk launch vs JIMM/IADS,

EA6B jamming IADS radar…

Ontology

Groups

18