1. Break Out Session on Infrastructure and Technology: A Report Vipul Kashyap AOS Workshop, Rome, 15 November 2001 vipul_kashyap@yahoo.com

2. Knowledge Acquisition Workshop – 2 Outline  A “Template” Architecture for the AOS System  Components of the Architecture  Tools, Techniques, Algorithms and Software for the Architecture  Recommendations: Priorities

3. Knowledge Acquisition Workshop – 3 User Query/ Information Request User Query/ Information Request User Query/ Information Request... DATA REPOSITORIES... DATA REPOSITORIES Information System 1 Information System N Integration Infrastructure (J2EE, Agents) Inter-Ontology Relationships Manager Ontology Server Ontology Server A “Template” Architecture for the AOS System

4. Knowledge Acquisition Workshop – 4 Components of the Architecture  Tools and Techniques for Ontology Building  Tools and Techniques to associate ontologies with underlying data  Technologies for Distributed Query Processing/Search  Tools and Techniques Distributed Ontology Integration/Interoperation  Tools and Techniques for Ontology Maintenance and Versioning  Integration Infrastructure  Back end technologies to store data and information repositories  User Interface Issues

5. Knowledge Acquisition Workshop – 5 Tools and Techniques for Ontology Building  Tools and Process for build ontology from scratch  Data Model Specific, e.g., EER, Object Oriented, RDF(S), DAML+OIL)  InfoSleuth Ontology Editor, OKBC Editor, Protégé, OntoEdit (Free and commercial), Ontology Builder  I-logix, Uniting Software Design, Tigris (UML based tools)  Open source tools available from http://www.semanticweb.org, http://www.daml.orghttp://www.semanticweb.orghttp://www.daml.org  Enhancement of Existing KOSs into domain specific ontologies  Enhancement of database schemas (relational, object oriented) to ontologies  ERWin: generates E-R models from database schemas  Enhancement of thesauri, glossaries, subject headings, controlled vocabularies, classification lists to develop ontologies  No known software tools  Design a process of inter-agency collaboration for building AOS based on existing KOSs –Process designed in the context of the EDEN System

6. Knowledge Acquisition Workshop – 6 Tools and Techniques to associate ontologies with underlying data  Tools for mapping ontological concepts to database schemas  OR mapping tools (J2EE suite)  InfoSleuth/EDEN mapping tools, Kaon-Reverse,  Tools for annotating documents (and fragments) with ontological concepts and relationships  IKA class of software, Onto-Mat  Tools for dealing with multi-lingual ontologies  E.g., OntoEdit, Kaon-Soep  Tools for annotating images with ontological concepts  No known software  Generation of Websites from Ontology  E.g., Semantic Miner  Data Mining/Classification/Ontology Learning Tools  E.g., Decision Tree based algorithms, C4.5, e.g., Whizbang!  Neural Networks, Statistical Clustering, Latent Semantic Indexing  Learning based annotation of documents  E.g., TextToOnto

7. Knowledge Acquisition Workshop – 7 Technologies for Distributed Query Processing/Search  Distributed indexing, meta-search –AGRIS multi-host search engine  Ontology-based, multi-resource distributed query processing (pull) –Federated database technology, e.g., Carnot, Mermaid, InfoSleuth/EDEN, Interbase  Ontology-based event notification and subscription (push) –E.g., InfoSleuth/EDEN agent-based approach, Oracle Triggers  Multimedia Search: e.g., specify query using image, get images, text documents, etc. –E.g., IBM, Virage

8. Knowledge Acquisition Workshop – 8 Tools and Techniques Distributed Ontology Integration/Interoperation  Tools for Mappings between various Thesauri and enabling their convergence –No Known Software  Tools for Ontology Brokering –No Known Software  Identification of inter-ontology terminological relationships –E.g., 20 candidate subject relationships for information retrieval  Identify the unit of re-use: –Inclusion of sub-ontologies, concepts, aggregations/reifications  Integration of community partner subject ontologies with the AOS ontology, tools for managing a federated ontology structure –No Known Software  Algorithm for query processing by re-using the above relationships (query re- writing) –E.g., ONION (Stanford), OBSERVER project –E.g., Protégé (Manual Merging for Ontologies, Stanford)

9. Knowledge Acquisition Workshop – 9 Tools and Techniques for Ontology Maintenance and Versioning  No Known Software  Tools and Techniques for maintenance of inter-ontological relationships –No Known Software

10. Knowledge Acquisition Workshop – 10 Integration Infrastructure  Component based technologies: –E.g., J2EE,.NET, COM  Agent based Systems –E.g., InfoSleuth/EDEN, FIPA  Markup/Representation languages –Agent-based, E.g., OKBC, KIF, KQML –Web-based, E.g., XML, RDF(S), DAML+OIL, DRDFS (based on conceptual graphs)  Web Services Technology –E.g., WSDL + UDDI + SOAP, ebXML  Important Criteria for evaluation: –Scalability, Performance, Fail Over, Recovery

11. Knowledge Acquisition Workshop – 11 Back end technologies to store data and information repositories  Structured Data –Relational Databases  E.g., Oracle, DB2, MySQL, SQL Server –Object Oriented Databases  E.g., ObjectStore, Versant, Poet  Textual Data –E.g., Verity, Documentum, Isis, Basis  Web Sites and Related Development Tools –Template driven websites, ASPs, JSPs…  Knowledge Bases for Ontology Storage and Inferencing –ICS-FORTH (RDF Suite, No inference), SESAME, 4SUITE, RDF-DB –E.g., KL-ONE Systems, CLASSIC, BACK, … –E.g., Allegra (Common Lisp based) –Object Oriented Databases –Relational Databases  Repositories for managing vocabularies and thesauri –E.g.. LEXICON, MultiTes, Knowledge Map

12. Knowledge Acquisition Workshop – 12 User Interface Issues  Type of Users –Browsing, Ontology-based Navigation, keywords –Exposure to query language. Eg.. SQL, DL?, TQML  Visualization –Ontologies  E.g., FRODO –Queries –Results

13. Knowledge Acquisition Workshop – 13 Priorities for Various Components  T&T for Ontology Building (1)  T&T for associating ontologies with underlying data (2)  User Interface and Visualization (3)  T&T for Multi-ontology interoperation (4)  T&T for Ontology (and Inter-Ontology Relationships) Maintenance and Versioning (5)  T&T Distributed Query and Search (6)  Underlying Integration Infrastructure (7)  Back End Technologies (8)

14. Knowledge Acquisition Workshop – 14 Criteria  Transaction/Scalability/Performance  Classification Accuracy  Open Source, Internationalization  Industry Standards/Interoperability  Easy to make future extensions –Multimedia –Other ontologies