EEL 5937 Ontologies EEL 5937 Multi Agent Systems Lecture 5, Jan 23 th, 2003 Lotzi Bölöni

EEL 5937 Ontology editor: Protégé-2000

EEL 5937 Protégé-2000 Developed at Stanford Medical Institute Java based ontology and knowledge base editor A tool which allows the user to: –construct a domain ontology –customize knowledge-acquisition forms –enter domain knowledge A platform which can be extended with graphical widgets for tables, diagrams, animation components to access other knowledge-based systems embedded applications; A library which other applications can use to access and display knowledge bases.

EEL 5937 Protégé-2000 as a library Public Java API allows procedural access to the knowledgebase: –Create, modify delete knowledgebases –Create, modify, delete classes and slots. –Create, modify, delete instances <-- this is how you will use it in your projects. Also allows access to the graphical elements of Protégé (e.g. forms).

EEL 5937 Protégé-2000: Backends Native format: –Clips inspired frame representation –Plain text, Lisp like language Plugins for backends: –XML storage backend –JDBC backend – storing the knowledgebase in a relational database –RDF backend Problems: –No support for concurrent access. –Simplistic mapping to relational databases. –Limited performance.

EEL 5937 Protégé-2000: Plugins PAL: Protégé Axiom Language –A superset of first order logic. –Can be used to express constraints about the knowledge base –Can be used to make queries about the knowledge base JessTab: integration with Jess –Jess is a Java based implementation of the Clips expert system shell. PROMPT: interactive ontology merging tool –Multiple ontologies: problems of mapping, refactoring etc. XML: – allows importing XML documents into Protégé-2000, creating a set of classes and instances dynamically. –Allows the saving of a Protégé-2000 database into XML.

EEL 5937 Project for a massive ontology: Cyc

EEL 5937 Cyc Founded by Doug Lenat (former professor at Carnegie Mellon and Stanford). Cyc software has been under development since 1984, founded mostly by government contracts. “We stand on the threshold of success” A knowledgebase of human common sense The Cyc knowledge base has an ontology of over 100,000 atomic terms axiomatized by a set of over 1 million handcrafted assertions stated in an n-th order predicate calculus employing over 10,000 predicates which are themselves first class terms in the knowledgebase.

EEL 5937 Cyc (cont’d) The Cyc inference engine includes general theorem provers but maintains efficiency by relying on a suite of over 500 heuristic level modules The knowledge base is divided into locally consistent contexts called micro-theories. Each micro-theory contains: –Content (a body of assertions) –Assumptions shared by those assertions The variant of the predicate calculus used to represent the assertions is a language called CycL. –Lisp syntax Interesting fact: they do not use neither fuzzy logic, nor probabilities

EEL 5937 OpenCyc open source version of the Cyc technology – Not quite completely open, knowledgebase is not listable, some tools are binary – Parts of the ontology (e.g. upper ontology) are available. Version 0.7beta released on December 17, 2002 It is implemented as a web-service. You start it as a process and browse it through your browser. You are encouraged to use it in your projects! (if you can find a use for it).

EEL 5937 Evaluation of the Cyc technology Ambitious, huge effort. Painstaking, slow knowledge engineering process. Probably, they have envisioned that the autonomous learning threshold will be reached much sooner. Questions: –Is the model correct? –Were the original assumptions correct? –If they were not, it would be very expensive to discover it now… Researchers outside have a mixed opinion. Using it is not trivial, exactly because of the size of the DB.

EEL 5937 DMTF / CIM

EEL 5937 DMTF / CIM Distributed management task force – an industry organization to promote the unification and adoption of management standards for desktop, enterprise and internet environments. – CIM: Common Information Model –“A model for describing overall management information in a network / enterprise environment” –Basically, an ontology under a different name CIM Specification –The language and style of the descriptions. –How to describe common patterns: relations, associations etc. –Mapping to other management models (e.g. SNMP) –Most of the CIM specifications are visually presented in UML. –They are formally expressed in MOF (Managed Object Format) – plain text, and quite similar to Clips.

EEL 5937 CIM Schemas The actual ontologies Core Schema is an information model that captures notions that are applicable to all areas of management Common Schemas are information models that capture notions that are common to particular management areas, but independent of a particular technology or implementation. The common areas are systems, devices, networks, applications, metrics, databases, the physical environment, event definition and handling, management of a CIM infrastructure (the Interoperability Model), users and security, policy and trouble ticketing/ knowledge exchange (the Support Model). Extension Schemas represent organizational or vendor- specific extensions of the Common Schema. These schemas can be specific to environments, such as operating systems (for example, Unix or Windows).