1. 0 DAML Tools for Intelligent Information Annotation, Sharing and Retrieval UMBC Johns Hopkins University Applied Physics Lab MIT Sloan School Tim Finin James Mayfield Benjamin Grosof DAML PI meeting, 30 November 2004

2. UMBC/JHU/MIT 11/19/2004 1/16 Intelligent Information Annotation, Sharing and Retrieval Overall Program Summary OWL enables agents in open, dynamic environments to share knowledge and cooperate on tasks while managing privacy, commitments, trust, and security. To do this, we must ensure that: – OWL integrates with common agent frameworks and standards – OWL integrates with other KR paradigms for real world reasoning -- rule based systems, Bayesian reasoning, etc. – OWL permits IR systems to index and retrieve documents with text, multimedia and knowledge Travel Agents Auction Service Agent Customer Agent Bulletin Board Agent Market Oversight Agent Request Direct Buy Report Direct Buy Transactions Bid CFP Report Auction Transactions Report Travel Package Report Contract Proposal Web Service Agents

3. UMBC/JHU/MIT 11/19/2004 2/16 Intelligent Information Annotation, Sharing and Retrieval Technical Problem and Approach Current agent systems are not set up to use OWL – Develop ontologies, conventions, software and tools to support using OWL in FIPA and similar systems – Demonstrate and investigate the use of OWL & Agents in realistic applications Policies need to be grounded in OWL content – Develop Rei as a declarative, RDF based policy language – Demonstrate via several testbeds OWL needs to be extended/integrated with rule-based reasoning – Work with groups to develop specifications for RuleML, SWRL, etc – Build prototype translation systems and demonstrations OWL needs to be extended/integrated with uncertainty reasoning – Annotate OWL content with Bayesian info and generate BBN – Demonstrate via support for ontology mapping We need information retrieval systems that work with RDF content – Augment existing IR systems like Google with swangle terms – Develop Swoogle as a native RDF search engine

4. UMBC/JHU/MIT 11/19/2004 3/16 Intelligent Information Annotation, Sharing and Retrieval Technical Progress Here are the comments on the template slide What technical problems were there and when/how did you overcome them? Are there any metrics that are relevant to your program? How did you measure technical progress and success? What were your intermediate goals? Did you meet your original or revised programmatic goals? We need to come with a slide for this

5. UMBC/JHU/MIT 11/19/2004 4/16 Intelligent Information Annotation, Sharing and Retrieval Milestones and Accomplishments Agent & Systems KR IR specs 2001 200220032004 2005 ITTALKSTAGA Vigil Soupa Cobra SweetJessSweetRules Rei F-OWL reasoner OWLIRSwoogle Swangler Bayes OWL DAML+OIL Joint Committee W3C WebOnt Working groupSWSI & SWSA Papers/ MS/PhD 5+/7?/2? 24/4/5 25/4/1 20/1/0 4/0/0 RGB s s s ss s s s s s Legend Software or service Ontology Ph.D. Dissertation Spec impact Distributed IDS Mogatu O OOO O O O RuleML O O O

6. 5 DAML Tools for Intelligent Information Annotation, Sharing and Retrieval http://daml.org/ UMBC, JHU/APL, and MIT/Sloan are working together on a set of issues to be integrated into agent-based applications involving search and using rule-based reasoning: UMBC: Integrating communicating agents, DAML and the Web; JHU APL: DAML and information retrieval; and MIT Sloan School: DAML, rules based technology and distributed belief Features Generation from DB to DAML and HTML mediated by MySQL, Java servlets, and JSP. Generation of DAML descriptions and user profiles from HTML forms. Creation & use of DAML-encoded user models describing interests and ontology extensions. Ontologies for events, people, places, schedules, topics, etc. Automatic HTML form (pre) filling from DAML. Syncing of talks with Palm calendars via Coola. Automatic classification of talks into topic ontology A XSB-based DAML/RDF reasoning engine. Agent-based services: ITTALKS agent with KQML API using DAML as content language Intelligent matching of people and talks based on interests, locations and schedules. Agents using both Jackal and FIPA’s Java Message Service Notification via email and mobile devices via SMS and WML. Discovery of relevant background papers from NEC CiteSeer Automatic generation and maintenance of user models Talk recommendations via collaborative filtering Integration with STP (Smart Things and Places) ubiquitous computing project UMBC AN HONORS UNIVERSITY IN MARYLAND Web server + Java servlets DAML reasoning engine DAML files Agents Databases People RDBMS DB Email, HTML, SMS, WAP FIPA ACL, KQML, DAML SQL HTTP, KQML, DAML, Prolog MapBlast, CiteSeer, Google, … HTTP HTTP, WebScraping Web Services Ittalks.org a database driven web site of IT related talks at UMBC and other institutions. The database contains information on –Seminar events –People (speakers, hosts, users, …) –Places (rooms, institutions, …) This database is used to dynamically generate web pages and DAML descriptions for the talks and related information and serves as a focal point for agent-based services relating to these talks. To add your organization to ittalks.org and receive a domain (e.g., mit.ittalks.org) contact info@ittalks.org. See http://daml.org/ for more information on DAML and the semantic web. info@ittalks.org Acknowledgements: Funded by DARPA, contract F30602-00-2-0591. Students: H. Chen, F. Perich, L. Kagal, S. Tolia, Y. Zou, J. Sachs, S. Kumar and M. Gandhe. Faculty: T. Finin, A. Joshi, Y. Peng, R. Cost, C. Nicholas, R. Masuoka http://ittalks.org/

7. 6 Travel Agent Game in Agentcities http://taga.umbc.edu/ Technologies FIPA (JADE, April Agent Platform) Semantic Web (RDF, OWL) Web (SOAP,WSDL,DAML-S) Internet (Java Web Start )Features Open Market Framework Auction Services OWL message content OWL Ontologies Global Agent Community Acknowledgements: DARPA contract F30602-00-2-0591 and Fujitsu Laboratories of America. Students: Y. Zou, L. Ding, H. Chen, R. Pan. Faculty: T. Finin, Y. Peng, A. Joshi, R. Cost. 8/03 Motivation Market dynamics Auction theory (TAC) Semantic web Agent collaboration (FIPA & Agentcities) Travel Agents Auction Service Agent Customer Agent Bulletin Board Agent Market Oversight Agent Request Direct Buy Report Direct Buy Transactions Bid CFP Report Auction Transactions Report Travel Package Report Contract Proposal Web Service Agents Ontologies Ontologies http://taga.umbc.edu/ontologies/ travel.owl – travel concepts fipaowl.owl – FIPA content lang. auction.owl – auction services tagaql.owl – query language FIPA platform infrastructure services, including directory facilitators enhanced to use DAML-S for service discovery

8. 7 Contributors include Tim Finin, Anupam Joshi, Yun Peng, R. Scott Cost, Jim Mayfield, Joel Sachs, Pavan Reddivari, Vishal Doshi, Rong Pan, Li Ding, and Drew Ogle. Partial research support was provided by DARPA contract F30602-00-0591 and by NSF by awards NSF-ITR-IIS-0326460 and NSF-ITR-IDM-0219649. November 2004. http://swoogle.umbc.edu/ Swoogle uses four kinds of crawlers to discover semantic web documents and several analysis agents to compute metadata and relations among documents and ontologies. Metadata is stored in a relational DBMS. Services are provided to people and agents. SWD Rank A SWD’s rank is a function of its type (SWO/SWI) and the rank and types of the documents to which it’s related. SWOs SWIs HTML documents Images CGI scripts Audio files Video files The web, like Gaul, is divided into three parts: the regular web (e.g. HTML), Seman- tic Web Ontologies (SWOs), and Semantic Web Instance files (SWIs) SWD = SWO + SWI Swoogle Statistics Swoogle puts documents into a character n- gram based IR engine to compute document similarity and do retrieval from queries SWD IR Engine SWOOGLE 2 SWD Metadata Web Service Web Server SWD Cache The Web Candidate URLs Web Crawler SWD Reader IR analyzerSWD analyzer Human users Intelligent Agents discovery digest analysis service Ontology Dictionary Swoogle Search Swoogle Statistics Ontology Dictionary Swoogle Search Swoogle provides services to people via a web interface and to agents as web services. SWDs310,000Classes95,000 Triples45,000,000Properties53,000 Ontologies4,200Individuals6,800,000 Statistics as of November 2004

9. 8 OWL Search using OWL document SwangleTool JENA OWL document + Swangled triples SwangleSearch Query Triple OWL document + Swangled triples OWLTriples Swangled text for [,, ] BE52HVKU5GD5DHRA7JYEKRBFVQ WS4KYRWMO3OR3A6TUAR7IIIDWA 2THFC7GHXLRMISEOZV4VEM7XEQ HO2H3FOPAEM53AQIZ6YVPFQ2XI 6P3WFGOWYL2DJZFTSY4NYUTI7I N656WNTZ36KQ5PX6RFUGVKQ63A IIVQRXOAYRH6GGRZDFXKEEB4PY Web Search Engine Filters Semantic Markup Inference Engine Local KB Semantic Markup Semantic Markup Extractor Encoder Ranked Pages Semantic Web Query Encoded Markup Text Query Text Filters Text [,, ] Inference [,, ] [,, ] [,, ] Swangler Vision Indexing and Search Swangler

10. 9 Student: Z. Ding. Faculty: Dr. Y. Peng, Dr. T. Finin, Dr. A. Joshi. Ack: DARPA Contract F30602-00-2-0591. 09/03. An example of translated Bayesian network ontology Unified Ontology Support using Bayesian Networks Motivation Reasoning within single ontologies is uncertain due to noisy or incomplete data DL based reasoning is overgeneralized and inadequate Relations between concepts in different ontologies are inherently uncertain OWL is the new standard proposed by W3C for ontology representation Translation Process Extending OWL for probability annotation Defining a set of structural translation rules to translate an OWL RDF graph to the directed acyclic graph (DAG) of Bayesian network (BN) Constructing conditional probability tables (CPTs) for individual variables in the DAG of BNApproach Translating OWL ontologies to Bayesian networks (BNs) Concept mapping as conditional probabilities Joining translated BNs (by probabilistic mappings) dynamically Support ontology reasoning (within and across ontologies) as Bayesian inference

11. Context Broker Architecture CoBrA Features [1] Use Semantic Web languages for context modeling and reasoning [2] Use logic inference to detect and resolve inconsistent context knowledge [3] Extend the REI policy language for privacy protection [4] Adopt the FIPA standards for communication & knowledge sharing EasyMeeting an intelligent meeting room prototype that provides services for speakers, audience & organizers based on their situational needs. http://cobra.umbc.edu

12. UMBC/JHU/MIT 11/19/2004 11/16 A slide on SweetRules, SWRL and RuleML Intelligent Information Annotation, Sharing and Retrieval Adding Rules to OWL

13. UMBC/JHU/MIT 11/19/2004 12/16 RGB: Research Group in a Box eating our own dog food The UMBC ebiquity lab’s portal exposes its content in RDF using a set of OWL ontologies for papers, people, projects, photos, etc. Lab members can add arbitrary RDF assertions about any of the portal’s objects. It’s designed as a modular, configurable package using O/S software that others can use to create their own portals.

14. UMBC/JHU/MIT 11/19/2004 13/16 Intelligent Information Annotation, Sharing and Retrieval Transition/Handoff Specifications – Participated in WEBONT, SWSA, SWSI, RuleML Software products – Damlator, Swangler, F-OWL, SweetRules, Rei Major demonstration systems – ITTALKS, TAGA, ebiquity site Services – Swoogle Papers – ~100 papers in journals, books, conferences and workshops, ~10 MS theses, 5 PhD dissertations Users – Swoogle has many users, Rei used by ~4 other groups, … more needed here

15. UMBC/JHU/MIT 11/19/2004 14/16 Intelligent Information Annotation, Sharing and Retrieval Remaining Issues IssueRemediation SweetRules plan not completed Complete design and implementation… Rei policy langu- age needs rules Incorporate SWRL/RuleML languages. Can we compile Rei policies to OWL+SWRL? Swoogle needs instance data Extend Swoogle’s database to include all instance data. But, how well will it scale? Swangler lacks query I/F Build a query interface for swangled Semantic Web documents. IR over mixed RDF and text Develop tools to enable Swangler and Swoogle to work with documents that embed RDF in XHTML. Bayes OWL demonstration Application to ontology mapping will require additional basic research. Can probabilities be estimated from Swoogle data? SweetRules toolkit Populate the SweetRules toolkit with open sourced implementations

16. UMBC/JHU/MIT 11/19/2004 15/16 Intelligent Information Annotation, Sharing and Retrieval Summary We’ve demonstrated that OWL enables agents in open, dynamic environments to share knowledge and manage privacy, commitments, trust, and security. – Demonstration: ITTALKS system, TAGA multiagent system, SOUPA ontology for pervasive computing OWL can be integrated with other KR paradigms for real world reasoning – Demonstration: SweetJess, SweetRules, Bayes OWL, Rei OWL is compatible with the information retrieval paradigm – Demonstration: Swoogle as an RDF search engine, Swangling permits IR systems to index and retrieve documents with text, multimedia, and knowledge. OWL facilitates the sharing of knowledge thru web portals – Demonstration: ebiquity web pages

17. UMBC/JHU/MIT 11/19/2004 16/16 Intelligent Information Annotation, Sharing and Retrieval Backup