Protégé An Environment for Knowledge- Based Systems Development Haishan Liu

Outline Things will be covered  The evolution of Prot é g é and the underlying driven idea  Major features of different versions of Prot é g é Things will not be covered  The detailed mechanisms and algorithms of the implementation

What is Protégé The Prot é g é system is an environment for knowledge-based systems development From a single tool to reduce the knowledge-acquisition bottleneck to a general-purpose environment for knowledge modeling

The classical model of expert system development

Difficulties in the classic model The knowledge engineer is involved in all phases of system construction  characterize the reasoning tasks  identify the major domain concepts  categorize the type of knowledge  identify the reasoning strategies used by experts,  define an inference structure for the resulting application,  and formalize all this knowledge in a generic and reusable way. domain experts are seen simply as resources for knowledge engineers to draw upon.

An early view: expert system shell Reuse of knowledge Base Knowledge acquisition is carried out by the knowledge engineer. The introduction of a knowledge engineer in between could lead to errors and misunderstandings. Time-consuming

Domain expert

Protégé Ancestry: Oncocin and Opal

Information-partitioning hypothesis structural domain concepts ① domain knowledge ② case data ③ ① ② ③

Advantage of Opal/Oncocin architecture Actual tools developed for knowledge acquisition The domain experts directly build the knowledge base  reduce the likelihood of errors  Streamline knowledge base construction

Protégé-I generalization of the Oncocin/Opal architecture

Assumptions of Protégé-I Problem specific KB  Only works well on certain PSMs Problem-solving method (PSM) provides semantics of KB  No formalization of the knowledge model Atomic PSM and KB  Self-contained KB (no reference to the others)  Single monolithic PSM

Summary of Protégé-I Generating knowledge-acquisition tools from structured meta-knowledge Neither reusable nor general purpose  Problem-specific KB  Lacking formal semantics

Protégé-II reusable problem-solving methods. A problem-solving method could be developed independently from the knowledge base. PSMs were generic algorithms that could be used with different knowledge bases to solve different real-world tasks.  constraint satisfaction  Classification  Planning  Bayesian inference

Problem-solving knowledge automates specific tasks Domain knowledge + Problem-solving method Intelligent behavior

Protégé-II Reusable problem-solving methods

Developing Knowledge-based Systems with Protégé-II Developing or reusing a problem-solving method Defining an appropriate domain ontology Generating a knowledge-acquisition tool Building a knowledge base using the tool Integrating these components into a knowledge-based system  defining mappings between problem-solving methods and specific knowledge bases.

Three classes of ontologies Domain ontologies (reusable)  define the concepts related to an application domain (e.g., different symptoms, anomalies, and remedies) Method ontologies (reusable)  specify the data requirements of the problem- solving methods (i.e., the input and output structure of each method) Application ontologies (application specific)  define the concepts that are specific to a particular application or implementation.

Protégé-II components for building knowledge bases. “Downhill Flow” Model Knowledge engineer Domain Expert

Integrating the Components of a Knowledge-Based System—Mappings KB and PSM are developed separately PSM may not match KB Use mapping relations to connect KB and PSM  Marble – a special KA tool to build mapping relations  A generic mapping interpreter producing adapted view of KB to PSM

Summary of Protégé-II Reusable PSMs as components Adoption of ontology Generation of KA-tools from any ontology “ Downhill Flow ” assumption of class over instance

Protégé/Win Besides the re-implementation The use of modular ontologies, via an ontology inclusion mechanism  build large knowledge bases by “ gluing ” together a set of smaller, modular ontologies  scale to large problems better than monolithic ontologies A more integrated, streamlined set of tools A more custom-tailoring knowledge- acquisition tool

Protégé-2000 significant augmentations Underlying knowledge model A single unified application A plug-in architecture

The Protégé-2000 Knowledge Model Protégé-Ihand-coded Lisp object Protégé-II and Protégé/Win a simple frame-based model provided by CLIPS Protégé-2000OKBC protocol Retrospect

Open Knowledge Base Connectivity (OKBC) Standard mechanism to access knowledge bases stored as “ frames ” of classes and attributes Adopted by several well-known knowledge- representation systems (Ontolingua, LOOM) Will allow Prot é g é to be used as an ontology- and knowledge-editing system for any OKBC-compliant server

OKBC – cont’d OKBC specifies a knowledge model of KRSs  with KBs, classes, individuals, slots, and facets It also specifies a set of operations based on this model  find a frame matching a name  enumerate the slots of a frame  delete a frame An application uses these operations to access and modify knowledge stored in a OKBC-compliant KRS.

The OKBC Knowledge Model Constants Frames Slots Facets Classes Individuals knowledge bases

Frames, slots and facets Frame  primitive object that represents an entity in the domain of discourse  Class Frame, Individual Frame Slot  Binary relation associate to a frame (describing the property of the frame) Facet  Constraints on the slot

The plug-in architecture of Protégé-2000

The OntoViz tab plug-in

A Protégé-2000 KA tool for entering rules for monitoring nuclear power plants

Elements of Protégé-2000 Slots as first-class objects Slots as first-class objects Classes and class hierarchy Classes and class hierarchy Facets standard and user-defined Facets standard and user-defined Instances Customizable instance forms Customizable instance forms Easy browsing Easy browsing Means to view large data sets Means to view large data sets Custom widgets Custom widgets Domain- specific tabs Domain- specific tabs Components for building knowledge-based applications Components for building knowledge-based applications