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Semantic Technologies I OMG Ontology Definition Metamodel Arbeitsgruppe Semantic Business Process Management Lecture 5 – Semantic Technologies I OMG Ontology Definition Metamodel Prof. Dr. Adrian Paschke Corporate Semantic Web (AG-CSW) Institute for Computer Science, Freie Universitaet Berlin [email protected] http://www.inf.fu-berlin.de/groups/ag-csw/ Problem: Only Syntactic BPM Models Lacks of Web Service Technology . Current BPM technologies allow usage of Web Services . But: . only syntactical information descriptions . syntactic support for discovery, composition and execution => Web Service usability, usage, and integration needs to be inspected manually . no semantically marked up content / services . no support for the Semantic Web rules and ontologies => current Web Service Technology Stack failed to realize the promise of Web Services Overview . Overview Semantic Technologies . Ontologies . OMG Ontology Definition Metamodel . W3C Web Ontology Language . Rules . OMG SBVR . OMG PRR . W3C RIF . RuleML Semantic Computing Technologies 4. Software Agents and Web-based Services . Rule Responder, FIPA, Semantic Web Services, … 3. Rules and Event/Action Logic & Inference . RIF, SBVR, PRR, RuleML, Logic Programming Rule/Inference Engines,… 2. Ontologien . ODM, CL, Topic Maps RDFS, OWL Lite|DL|Full, OWL 2, … 1. Explicit Meta-data and Terminologies . vCard, PICS, Dublin Core, RDF, RDFa, Micro Formats, FOAF, SIOC … 1. Explicit Metadata on the Web . Metadata are data about data . Metadata on the Web: . Machine processable information about information on the Web . Projects . e.g., PICS, Dublin Core, RDF, FOAF, SIOC, … . Problem domains: . Syntax: . Which representation and interchange format for metadata? . Semantics: . Which metadata are allowed for resources (metadata vocabulary, schema) . Association problem: . How to connect metadata with resources (who defines the metadata, are metadata separated from the content, etc.) 2. Ontologies . “An ontology is an explicit specification of a conceptualization “ T. Gruber . Ontologies described the common knowledge of a domain (semantics): Semantics interoperability between (connected) vocabularies . Typical components: 1. Classes (concepts) of the domain 2. Properties (roles) of the classes 3. Constraints 4. Individuals (instances) of classes 3. Rules (Logic and Inference) . Logic is a discipline concerned with the principles of inference and reasoning . Formal languages for the representation of knowledge with clear semantics . Declarative knowledge representation: express what is valid, the responsibility to interpret this and to decide on how to do it is delegated to an interpreter / reasoner . Automated reasoner, e.g., a rule engine, can derive conclusions from given knowledge (inference) 4. Software Agents and Semantic Web Services . Intelligent Software Agents act autonomously and pro-active . They have an internal knowledge base with decision/reaction logic (e.g. rule-based expert systems) . Examples: Personal agents (e.g. Rule Responder), search robots . Web Service . In general: any IT service provided on the Web . “A 'Web service' (also Web Service) is defined by the W3C as "a software system designed to support interoperable Machine to Machine interaction over a network." Web services are frequently just Web APIs that can be accessed over a network, such as the Internet, and executed on a remote system hosting the requested services.” (Wikipedia) . => no clear separation between web agents and web services (in the broad sense) . but level of self-autonomous decisions is higher in web agents Ontologies Aristotle - Ontology . Before: study of the nature of being . Since Aristotle: study of knowledge representation and reasoning . Terminology: . Genus: (Classes) . Species: (Subclasses) . Differentiae: (Characteristics which allow to group or distinguish objects from each other) . Syllogisms (Inference Rules) [Aristotle] Science of Being, Methapysics, IV, 1 What is an Ontology? (in IT) An Ontology is a formal specification Executable, Discussable of a shared Group of persons conceptualization About concepts; abstract class of a domain of interest e.g. an application, a specific area, the “world model” [Gruber 1993] - T.R. Gruber, Toward Principles for the Design of Ontologies Used for Knowledge Sharing, Formal Analysis in Conceptual Analysis and Knowledge Representation, Kluwer, 1993. Requirements for Ontology Languages . Ontology languages allow users to write explicit, formal conceptualizations of domain models . The main requirements are: . a well-defined syntax . efficient reasoning support . a formal semantics . sufficient expressive power . convenience of expression Concept - Instance . Concept / Class / Universal (Metaphysics) . an abstract or general idea inferred or derived from specific instances Person . Instance / Individual / Particular (Metaphysics) . object in reality, a copy of a abstract concept with actual values for properties Person Name: Adrian Paschke Teaches: Computer Science LivesIn: Berlin WorksAt: Freie Universität Berlin Types of ontologies [Guarino et al. 1999] - N. Guarino, C. Masolo, G. Vetere. OntoSeek: Content-Based Access to the Web. In: IEEE Intelligent Systems, 14(3), 70--80, 1999. Taxonomy Object Person Topic Document Student Researcher Letter Movie Doctoral Student PhD Student . Taxonomy := Segmentation, classification and ordering of elements into a classification system according to their relationships Thesaurus Object Person Topic Document related to Student Researcher Letter Email similar Doctoral Student PhD Student synonym . Terminology for a specific domain . Taxonomy plus fixed relationships (similar, synonym, related to) . originate from bibliography Topic Map Object knows described_in Person Topic Document related to writes Student Researcher Letter Email similar Doctoral Student PhD Student synonym Tel Affiliation . Topics (nodes), relationships, and occurrences of documents . ISO-Standard . typically for navigation and visualisation Ontology (in our sense) Object is_a-1 is_a-1 knows described_in Person Topic Document related_to -1 -1 is_a is_a -1 -1 is_a is_a writes Student Researcher Letter Email is_similar_to is_a-1 is_a-1 Affiliation RULES, e.g.: Doctoral Student described_in is_about PhD Student instance_of-1 T D T D writes is_about knows Hans Muster P D T P T Tel Affiliation +49 030 608 …. FUB . Representation Languages: ODM, RDF(S); OWL; Predicate Logic; F-Logic, ISO CL,… Formality of KR Languages Many Ontology Languages No special ontolgy languages, but might be used to describe . Entity Relationship Modell ontologies . UML with OCL . Frames . Predicate Logic . Common Logic . Description Logic (formal Semantics, Reasoning) . SHOE, XOL, OML, SKOS, OBO . RDFS, DAML+OIL -> OWL . ODM . … Ontologies and their relatives Based on AAAI’99 Ontologies Panel – McGuiness, Welty, Ushold, Gruninger, Lehmann Ontologies and their relatives (2) Standards/Recommendations/Specifications for Semantic Computing ISO/IEC Terminology Object Semantic 11179 Management Web Metadata Registries Graph RDF(S) / OWL Metadata Registry Node Subject CONCEPT MOF Terminology Thesaurus Refers To Symbolizes Taxonomy ODM Ontology Edge Predicate “Rose”, PRR Data Structured Stands For “ClipArt Metadata Standards Referent Rose” SBVR Node Object RIF ISO/IEC JTC 1/SC 32 ISO TC 37 OMG W3C 24 Ontology Definition Metamodel OMG ODM OMG Ontology Definition Metamodel (ODM) . ODM is the OMG standard for model driven ontology development . Adopted as an OMG standard in October 2006 . http://www.omg.org/cgi-bin/doc?ptc/2007-09-09 . Not one model, but a family of metamodels . Supports exchange of independently developed models . Provides standard profiles for ontology development in UML . Enables consistency checking and validation of models in general Ontology Definition Metamodel . ODM brings together the communities by providing: . Broad interoperation within Model Driven Architecture . MDA tool access to ontology based reasoning capability . UML notation for ontologies and ontological interpretation of UML OMG MOF and OMG MDA Excurse OMG MOF . The Meta-Object Facility (MOF) is an Object Management Group (OMG) standard for model-driven engineering. M0 Layer . Concrete representation of data. M1 Layer . Models, e.g. knowledge models, process modes, UML / object models, which define the data on the M0 layer. M2 Layer . Meta-Models. Define the structure and architecture of models. M3 Layer . Meta-Meta-Models (MOF layer). Abstract layer, which is used to define the M2 layer. MOF-Based Metadata Management . MOF tools use metamodels to generate code that manages metadata, as XML documents, CORBA objects, Java objects . Generated code includes access mechanisms, APIs to . Read and manipulate . Serialize/transform . Abstract the details based on access patterns MOF . Related standards: . XML Metadata Interchange (XMI®) . CORBA Metadata Interface (CMI) . Java Metadata Interface (JMI) . Metamodels are defined for . Relational and hierarchical database modeling . Online analytical processing (OLAP) . Business process definition, business rules specification . XML, UML, and CORBA ID OMG MDA . OMG Model-driven Architecture (MDA) is a kind of domain engineering, and supports model- driven engineering (MDE) 1. Computation Independent Model (CIM) 2. Platform Independent Model (PIM) 3. Platform Specific Model (PSM) . Insulates business applications from technology evolution, for . Increased portability and platform independence . Cross-platform interoperability . Domain-relevant specificity OMG MDA - MOF . Consists of standards
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