Intent of Work

Program: DARPA Agent Markup Language

Project: UML-Based Ontology Toolset (UBOT)

Contract No. F30602-00-C-0188

Period covered: January 2003 – September 2003

Prepared by: Paul Kogut

Lockheed Martin Management and Data Systems

paul.a.kogut@lmco.com

610-354-3524

Date: November 29, 2002

DAML Experiment

Technical Goals:

Build applications to help understand practical issues with DAML/OWL and support transition of the Semantic Web to C4ISR domains. Specific tasks include:

· Extend the 2002 DAML-S ISR agent prototype for use by military planners with realistic data. This would include:

· adding more agents, ontologies and data sources

· enhancements to take advantage of new versions of DAML-S, DAML time and geographical ontologies, DAML query and DAML rules

· experiments with matchmaking that leverages the service category in DAML-S

· experiments with automatic composition of services

· adding an imagery/map browser

· Tailor AeroDAML to generate markup of sources that would support tactical extensions of SONAT (e.g., doctrine, commanders guidance, C2 chat rooms).

Metrics:

• Size/complexity of ISR ontologies and DAML-S profile and process models
• precision and recall for DAML-S matchmaking

Next Logical Steps:

• Integrate DAML-S ISR agents with mobile agents developed by Lockheed Martin Advanced Technology Labs for the DARPA CoABS program for tactical environments.

DAML Markup Tools

Technical Goals:

Extend and refine domain independent markup tools to foster wide acceptance of the Semantic Web. Specific tasks include:

• Modify AeroDAML to generate OWL markup.
• Add new AeroDAML capability for one-step markup generation of multiple webpages (e.g., entire websites).
• Add more general interest target ontology choices to AeroDAML. Candidate ontologies include: DAML-time and DAML-space(geographical).
• Expand the markup generation coverage of AeroDAML by integrating the AeroText knowledge base developed for Horus.
• Extend the tool that allows the user to customize AeroDAML markup generation by mapping the default ontology to a user-defined ontology.
• Investigate tools and techniques to support mixed initiative human-in-the-loop markup.
• Investigate approaches based on consistency reasoning for co-reference resolution of instances between multiple webpages.
• Collaborate with the Horus team to apply the AeroText-based Automated Markup Tool to the Intelink domain (funded separately by the Horus program).

Metrics:

• Recall – number of instances annotated (class instances and property instances) divided by the number of instances that exist in the document expressed as a percentage
• Precision - number of instances correctly annotated (class instances and property instances) divided by the number of instances that were annotated expressed as a percentage
• Coverage - % of classes and properties in a given ontology that can be automatically marked-up.

Next Logical Steps:

• Investigate the relationships between markup metrics (recall, precision, and coverage) and the type of DAML application/query.

· Investigate tools and techniques for reducing the effort required for tailoring tools to generate domain specific markup.

Semantic Web Application Engineering

Technical Goals:

Develop a quantitative framework for understanding the query capability vs. scalability tradeoff for Semantic Web reasoning infrastructures. This framework will support design decisions for Semantic Web applications in the C4ISR domain. Specific tasks include:

• Develop benchmark query set and scalability metrics.
• Investigate hybrid reasoning infrastructures that have promising query/scalability characteristics.
• Conduct experiments based on framework to compare widely available and hybrid reasoning infrastructures. Candidate reasoning infrastructures include: Parka, XSB, Jess, SNARK, JTP.

Metrics:

• Size/complexity of benchmark query set
• Query response time for hybrid reasoning infrastructure
• Number of reasoning infrastructures evaluated against the framework

Next Logical Steps:

• Apply the framework to support design decisions for Semantic Web applications in the C4ISR domain.

Consistency Checking Tools for the Semantic Web

Technical Goals:

Extend and refine tools that will improve the quality of ontologies and markup and support fusion of Semantic Web information for C4ISR applications. Specific tasks include:

· Extend the consistency reasoning agent to check OWL ontologies and markup and DAML rules.

· Investigate approaches based on consistency reasoning for co-reference resolution of instances between multiple webpages. This supports fusion of Semantic Web information.

· Continue to provide candidate revisions to the DAML axiomatic semantics specification as a byproduct of formally modeling DAML with Specware and theorem proving with SNARK.

Metrics:

• % of known errors found (use test ontologies with manually seeded errors)
• % of errors found in ontologies that are legitimate errors
• processing time required to check ontologies related to size/complexity of ontology

Next Logical Steps:

· Integrate consistency reasoning based fusion approaches into a C4ISR application.

· Integrate consistency reasoning agent with tools to support development of C4ISR agent applications.