Semantic Web for the Military User Progress

Tom Martin

Research Management Enterprises

[email protected]

(571) 215-9802

Slide 2

Semantic Web for the Military User
Meetings

SWMU II – Nov 12/13 2001

Agenda

Attendees

Approach

Outcome – Working Session Results

Joint SWMU/GMUG/EEE Meeting March 25-27, 2002

Background

Rationale for Joint Meeting

Objectives

Approach/Agenda

SWMU II Agenda

Tuesday, November 12, 2001

AM – Introduction for those who had not attended SWMU-I (June 2001)

Ontologies Introduction, Horus Overview, DAML Language, Example Demo IT Talks, & Summary of Last Meeting (SWMU-I)

PM – Plenary for all attendees

Update of DAML

Several short DAML demos – BBN, DRC, and LM AeroText

CoABS Grid Military Users Group (GMUG) overview

Horus update

NWDC updates,

Updates from Breakout groups:

Intelligence (Joe Rockmore)

Doctrine/Lessons Learned (Alice Mulvehill)

C2 Applications (Tom Martin)

Evening Demo session

Wednesday, November 13, 2001

Intel, Doctrine/LL, and C2 Breakouts and Outbriefs

SWMU II Attendee/Organizations

Elaine Marsh/NRL

Frank Muller/BBN

Paul Kogut/Lockheed-Martin

Joe Rockmore/Cyladian

Mike Dean/BBN

Rob Rasch/BCBL-L (Army)

Mike Rimmer/NWDC

Mark Gorniak/AFRL

Ken Whitebread/LMSC/ATL

Frank White/SSC

Martha Kahn/Global Infotek

Hal Hultgren/NWDC

Paul Neves/BBN

Lee Lacy/DRC

Tom Martin/RME

Alice Mulvehill/BBN

Wayne Perras/NWDC

Intelligence Breakout
Joe Rockmore - Facilitator

Charter

How do the ideas of the semantic web specifically apply to intelligence problems?

What unique problems does the intelligence community have with respect to using semantic web technology?

How can we leverage the work being done in DAML, and specifically the applications to intelligence, to other efforts?

Semantic Web
Functional Architecture

Intelligence Ontologies
(vice C2, logistics, or others)

Intelligence needs to talk about what was, is, and might be (with uncertainty), while C2 plans what to do with resources available, logistics makes resources available, etc.

Ontologies need to reflect differences in data and mission

Issues of interest to intelligence (primary)

Money laundering, geopolitical issues, financial transactions, non-military organizations, drugs, counter-terrorism, etc.

Imagery, signals, open source, & analysis of this data

Generally higher levels of abstraction than C2, etc.

Source info and confidence in source important

Temporal and spatial reasoning important

Significant Issue: Geolocation & Temporal Representation

Understand documents enough to know locations in a document

Placename, lat/lon, BE num, UTM, etc.

Disambiguation

Granularity issues

Understand documents enough to know temporal aspects in a document

Absolute time in different granularity (date & time to milliseconds vs. season) and representations (Julian date, DTG, etc.)

Disambiguation

Relative time (before, after, within, overlapping, close to, etc.)

Co-reference problems in geolocations and times

Significant Issue:
Markup Tools

Consumer-based and producer-based markup tools needed

Combine automated and manual markup intelligently

Markup as part of authoring

Culture is analysts (producers) are too busy to do any additional work, such as markup, unless

Its very easy to do

There is clear value to producers (not just consumers)

Someone measures them on the quality/quantity of markup

Mid term: mixed initiative, where authoring and knowledge object creation are done in parallel and with either driving the process

A long term view: author knowledge objects from the outset; form products from these objects, including English text documents

Multilingual opportunities

Significant Issue:
Access to Data

Tailored push; also pull (“My Intelink”), including changes of sufficient magnitude

Subscriptions and data descriptions for matching against subscriptions may be best done using hierarchical ontologies (vice database schemata, which are not sufficiently expressive)

Crawlers of value, but may have access control issues (open source an exception)

Uncertainty of data (both by source and about source)

Inference-based retrieval of information

Pedigree critical to maintain (but often raises the security levels)

Indexing of markup important for speed of access

Timelines for intelligence information.

Can be long, if national

Can be short, if tactical

Significant Issue:
Collection

Tie collection, processing, production together

A common markup language will enhance collection, thus optimizing use of intel resources

Producers and consumers have different ways of looking at the world; there is not necessarily a mapping between them

Can consumers provide tasking to producers, via markup, of requirements on collection?

Info data needs from UJTL tasks or other statement of data needs

Significant issue:
Security

Will DAML markup allow semantic understanding of information enough to affect releasability processes?

Can we do our collection and analysis at SCI and report at lower levels (including collateral , coalition, and unclass)?

Recommendations

Military and intelligence users that particularly should hear about semantic web:

DoD elements: DIA (esp JIVA), NSA

Agencies: NRO, NIMA, CIA

Service intel agencies: ISCOM, AFIA, ONI, MCIA

Unified commands: JIC’s and JAC’s

Standards setting and interoperability orgs

How do organizations understand what DAML products and approaches could help them?

Focused TIE’s with appropriate producers and consumers around specific value propositions

Doctrine/Lessons Learned:
Breakout Session Out-Brief

Some Common Goals

Significant Issues/Needs

Questions

Recommendations/Plan of Action

C2 Applications
Facilitator – Tom Martin

Objectives

Explore Command and Control Applications for DAML developments, both long and short term

What are ways in which we can best explore the value of DAML for C2 functions

DAML in Expeditionary Sensor Grid
(ESG) for Data and Information Fusion

DAML in Sensor Fusion

By the way

XML = 10x hard code

DAML = 2x XML

Jini/Java breakpoint

Recommendations/Actions

Communications

For ESG, smart agent needed for dynamic communications management to do reasoning about the network – to support the smart agent operation, need:

Comms ontology from Operational Level to Tactical Level (see next slide)

Identify boundaries of sensor nets, etc.

Ontology Development

Ontology from Operational Level (CJTF) to tactical level (weapons on target) for supporting modeling of sensor/ communications/ information management needs

Benefits to ESG

Experiment design

System Concept Testing

Once refined, system design, and construction

Ties to many many other needs

Intelligence, Leverage of Doctrine/TTP/Lessons Learned/Training work

Experimentation

Experimentation (General)

For both Communications and Fusion applications, refine the CoABS Grid DAML interfaces for Utility for

Dynamic Communications

Sensor Management

Sensor Fusion

DAML for Fusion

EEE Experimentation

Explore the Depth of where DAML markup makes the most sense

Explore Jini/Java (I.e., Grid) object translation to DAML

Research

Assess DAML tools for the multiple layers from the physical to the information management

Bandwidth tradeoffs, etc.

Modeling DAML/assessing utility in the mobile environment

Joint SWMU/GMUG/EEE
March 25-25, 2002
SPAWAR Systems Center, San Diego, CA

A new approach to the Agent Based Computing

Outreach to Transition Partners

Joint SWMU/GMUG/EEE March 25-27, 2002
Background

Vision of Future Warfare

Fit to ESG/Interest of Navy in Agent Based Computing

Agent-Based and DARPA Fusion Technology Roles

CoABS Grid

Semantic Web/DAML

DDB/DTT

Each Program at a turning point

Changes of the Military Environment

Changes of Management and Organization

Joint SWMU/GMUG/EEE
Rationale for Joint Meeting

Unprecedented Opportunity

Fruition of DARPA Technologies

Role of NWDC in ESG Experimentation

FY 01 Accomplishments with CoABS Grid

Interoperability

Dynamic Reconfigurability

Security

FY 02 Plans

Distributed Multiple “Real” vs. Virtual Sensors

Teaming with JBI and possibly AATD

Fusion efforts – DDB/AIM and DAML

Joint Meeting Rationale

Many of Same Participants for all Three Meetings

Sharing with Those Greatest Stressing the Technologies

Opportunity Joint Work on Future

Joint SWMU/GMUG/EEE
Objectives

Review ESG Enabling Experiment Plans

Expose non-EEE Participants to key use of ABC

NWDC Explore Added Opportunities for Co-evolve Emerging Technologies with New Concepts and Doctrine

Adjust/Refine EEE Plans Accordingly

A Forum for Sharing Grid and Semantic Web Experiences

Review of Key Lessons Learned

Challenges, Problems, Work-arounds

Feed Back to Developers and Program Managers

Explore Potential for Key ABC and Fusion Technologies to Contribute to ESG/JBI in Future

Identify Potential DARPA Initiatives to Address Unsolved Technology Issues

Result in actionable Plan of Action and Milestones to meet those objectives above

Joint SWMU/GMUG/EEE
Approach

Joint meeting for all three groups

Sequence

Objectives and Sponsor Views

ONR/NWDC Objectives

DARPA – CoABS, DAML, DDB/AIM

Users Reviews

EEE Plans and Progress, and Grid Lessons Learned

DAML Issues, NWDC Lessons Learned/Doctrine CALL

Horus, AATD, CECOM, AFRL/JBI

Working Groups

Joint SWMU/GMUG/EEE
Working Group Process

4 Focus Areas

Connectivity, Interoperability, and Security (SSC and JBI Lead)

Sensors, Fusion, and Representation Using DARPA Technologies (SSC Lead)

Highlight DARPA Projects CoABS Grid, DAML, and DDB/AIM

Agents for C2 (NWDC Lead)

Ontologies for Military Use – Representation, C2, Fusion, Military Lessons Learned, Doctrine, Intelligence (NWDC Lead)

Objectives

Focus – Issues, Problems, Lessons Learned, Opportunities

Objective, POA&M with with responsibilities, milestones, and due dates assigned

Interrelated, not stove-piped approaches and solutions

Joint SWMU/GMUG/EEE
Overall Process

Joint SWMU/GMUG/EEE - Working Group Process – Interim Briefing – Cross Pollination

Joint SWMU/GMUG/EEE - Working Group Process – Final POA&M’s – Interrelated

Joint SWMU/GMUG/EEE
Schedule

Joint SWMU/GMUG/EEE
Outcome


	Tom Martin
	Research Management Enterprises
	[email protected]
	(571) 215-9802


	SWMU II – Nov 12/13 2001
		Agenda
		Attendees
		Approach
		Outcome – Working Session Results
	Joint SWMU/GMUG/EEE Meeting March 25-27, 2002
		Background
		Rationale for Joint Meeting
		Objectives
		Approach/Agenda


Tuesday, November 12, 2001
	AM – Introduction for those who had not attended SWMU-I (June 2001)
		Ontologies Introduction, Horus Overview, DAML Language, Example Demo IT Talks, & Summary of Last Meeting (SWMU-I)
	PM – Plenary for all attendees
		Update of DAML
		Several short DAML demos – BBN, DRC, and LM AeroText
		CoABS Grid Military Users Group (GMUG) overview
		Horus update
		NWDC updates,
		Updates from Breakout groups:
			Intelligence (Joe Rockmore)
			Doctrine/Lessons Learned (Alice Mulvehill)
			C2 Applications (Tom Martin)
	Evening Demo session
Wednesday, November 13, 2001
	Intel, Doctrine/LL, and C2 Breakouts and Outbriefs


	Elaine Marsh/NRL
	Frank Muller/BBN
	Paul Kogut/Lockheed-Martin
	Joe Rockmore/Cyladian
	Mike Dean/BBN
	Rob Rasch/BCBL-L (Army)
	Mike Rimmer/NWDC
	Mark Gorniak/AFRL
	Ken Whitebread/LMSC/ATL
	Frank White/SSC
	Martha Kahn/Global Infotek
	Hal Hultgren/NWDC
	Paul Neves/BBN
	Lee Lacy/DRC
	Tom Martin/RME
	Alice Mulvehill/BBN
	Wayne Perras/NWDC


	Charter
		How do the ideas of the semantic web specifically apply to intelligence problems?
		What unique problems does the intelligence community have with respect to using semantic web technology?
		How can we leverage the work being done in DAML, and specifically the applications to intelligence, to other efforts?


	Intelligence needs to talk about what was, is, and might be (with uncertainty), while C2 plans what to do with resources available, logistics makes resources available, etc.
		Ontologies need to reflect differences in data and mission
	Issues of interest to intelligence (primary)
		Money laundering, geopolitical issues, financial transactions, non-military organizations, drugs, counter-terrorism, etc.
		Imagery, signals, open source, & analysis of this data
	Generally higher levels of abstraction than C2, etc.
	Source info and confidence in source important
	Temporal and spatial reasoning important


	Understand documents enough to know locations in a document
		Placename, lat/lon, BE num, UTM, etc.
		Disambiguation
		Granularity issues
	Understand documents enough to know temporal aspects in a document
		Absolute time in different granularity (date & time to milliseconds vs. season) and representations (Julian date, DTG, etc.)
		Disambiguation
		Relative time (before, after, within, overlapping, close to, etc.)
	Co-reference problems in geolocations and times


	Consumer-based and producer-based markup tools needed
		Combine automated and manual markup intelligently
		Markup as part of authoring
	Culture is analysts (producers) are too busy to do any additional work, such as markup, unless
		Its very easy to do
		There is clear value to producers (not just consumers)
		Someone measures them on the quality/quantity of markup
	Mid term: mixed initiative, where authoring and knowledge object creation are done in parallel and with either driving the process
	A long term view: author knowledge objects from the outset; form products from these objects, including English text documents
	Multilingual opportunities


	Tailored push; also pull (“My Intelink”), including changes of sufficient magnitude
		Subscriptions and data descriptions for matching against subscriptions may be best done using hierarchical ontologies (vice database schemata, which are not sufficiently expressive)
	Crawlers of value, but may have access control issues (open source an exception)
	Uncertainty of data (both by source and about source)
	Inference-based retrieval of information
	Pedigree critical to maintain (but often raises the security levels)
	Indexing of markup important for speed of access
	Timelines for intelligence information.
		Can be long, if national
		Can be short, if tactical


	Tie collection, processing, production together
	A common markup language will enhance collection, thus optimizing use of intel resources
	Producers and consumers have different ways of looking at the world; there is not necessarily a mapping between them
		Can consumers provide tasking to producers, via markup, of requirements on collection?
		Info data needs from UJTL tasks or other statement of data needs


	Will DAML markup allow semantic understanding of information enough to affect releasability processes?
		Can we do our collection and analysis at SCI and report at lower levels (including collateral , coalition, and unclass)?


	Military and intelligence users that particularly should hear about semantic web:
		DoD elements: DIA (esp JIVA), NSA
		Agencies: NRO, NIMA, CIA
		Service intel agencies: ISCOM, AFIA, ONI, MCIA
		Unified commands: JIC’s and JAC’s
		Standards setting and interoperability orgs
	How do organizations understand what DAML products and approaches could help them?
		Focused TIE’s with appropriate producers and consumers around specific value propositions


Objectives
	Explore Command and Control Applications for DAML developments, both long and short term
		What are ways in which we can best explore the value of DAML for C2 functions


	For ESG, smart agent needed for dynamic communications management to do reasoning about the network – to support the smart agent operation, need:
		Comms ontology from Operational Level to Tactical Level (see next slide)
		Identify boundaries of sensor nets, etc.


Ontology from Operational Level (CJTF) to tactical level (weapons on target) for supporting modeling of sensor/ communications/ information management needs
	Benefits to ESG
		Experiment design
		System Concept Testing
		Once refined, system design, and construction
	Ties to many many other needs
		Intelligence, Leverage of Doctrine/TTP/Lessons Learned/Training work


Experimentation (General)
	For both Communications and Fusion applications, refine the CoABS Grid DAML interfaces for Utility for
		Dynamic Communications
		Sensor Management
		Sensor Fusion
DAML for Fusion
	EEE Experimentation
		Explore the Depth of where DAML markup makes the most sense
		Explore Jini/Java (I.e., Grid) object translation to DAML
	Research
		Assess DAML tools for the multiple layers from the physical to the information management
			Bandwidth tradeoffs, etc.
		Modeling DAML/assessing utility in the mobile environment


	A new approach to the Agent Based Computing
	Outreach to Transition Partners


Vision of Future Warfare
	Fit to ESG/Interest of Navy in Agent Based Computing
	Agent-Based and DARPA Fusion Technology Roles
		CoABS Grid
		Semantic Web/DAML
		DDB/DTT
		Each Program at a turning point
			Changes of the Military Environment
			Changes of Management and Organization


Unprecedented Opportunity
	Fruition of DARPA Technologies
	Role of NWDC in ESG Experimentation
	FY 01 Accomplishments with CoABS Grid
		Interoperability
		Dynamic Reconfigurability
		Security
	FY 02 Plans
		Distributed Multiple “Real” vs. Virtual Sensors
		Teaming with JBI and possibly AATD
		Fusion efforts – DDB/AIM and DAML
Joint Meeting Rationale
		Many of Same Participants for all Three Meetings
		Sharing with Those Greatest Stressing the Technologies
		Opportunity Joint Work on Future


Review ESG Enabling Experiment Plans
	Expose non-EEE Participants to key use of ABC
	NWDC Explore Added Opportunities for Co-evolve Emerging Technologies with New Concepts and Doctrine
	Adjust/Refine EEE Plans Accordingly
A Forum for Sharing Grid and Semantic Web Experiences
	Review of Key Lessons Learned
		Challenges, Problems, Work-arounds
		Feed Back to Developers and Program Managers
Explore Potential for Key ABC and Fusion Technologies to Contribute to ESG/JBI in Future
Identify Potential DARPA Initiatives to Address Unsolved Technology Issues
Result in actionable Plan of Action and Milestones to meet those objectives above


Joint meeting for all three groups
Sequence
	Objectives and Sponsor Views
		ONR/NWDC Objectives
		DARPA – CoABS, DAML, DDB/AIM
	Users Reviews
		EEE Plans and Progress, and Grid Lessons Learned
		DAML Issues, NWDC Lessons Learned/Doctrine CALL
		Horus, AATD, CECOM, AFRL/JBI
	Working Groups


4 Focus Areas
	Connectivity, Interoperability, and Security (SSC and JBI Lead)
	Sensors, Fusion, and Representation Using DARPA Technologies (SSC Lead)
		Highlight DARPA Projects CoABS Grid, DAML, and DDB/AIM
	Agents for C2 (NWDC Lead)
	Ontologies for Military Use – Representation, C2, Fusion, Military Lessons Learned, Doctrine, Intelligence (NWDC Lead)
Objectives
	Focus – Issues, Problems, Lessons Learned, Opportunities
	Objective, POA&M with with responsibilities, milestones, and due dates assigned
	Interrelated, not stove-piped approaches and solutions