Metamodels for RDF Schema and OWL

Similar documents
Position Paper W3C Workshop on RDF Next Steps: OMG Ontology PSIG

Table of Contents. iii

Semantic Web Domain Knowledge Representation Using Software Engineering Modeling Technique

Integration of the Semantic Web with Meta Object Facilities

The Model-Driven Semantic Web Emerging Standards & Technologies

AT&T Government Solutions, Inc.

MDA & Semantic Web Services Integrating SWSF & OWL with ODM

OMG Specifications for Enterprise Interoperability

OWL a glimpse. OWL a glimpse (2) requirements for ontology languages. requirements for ontology languages

Automation of Semantic Web based Digital Library using Unified Modeling Language Minal Bhise 1 1

Semantic Technologies

Model Driven Ontology: A New Methodology for Ontology Development

FOUNDATIONS OF SEMANTIC WEB TECHNOLOGIES

Semantic Web. Ontology and OWL. Morteza Amini. Sharif University of Technology Fall 95-96

The Semantic Web RDF, RDF Schema, and OWL (Part 2)

WHY WE NEED AN XML STANDARD FOR REPRESENTING BUSINESS RULES. Introduction. Production rules. Christian de Sainte Marie ILOG

Models versus Ontologies - What's the Difference and where does it Matter?

TMCL and OWL. Lars Marius Garshol. Bouvet, Oslo, Norway

Event Metamodel and Profile (EMP) Proposed RFP Updated Sept, 2007

9 The Ontology UML Profile

Modelling in Enterprise Architecture. MSc Business Information Systems

Ontological Modeling: Part 2

Ontological Modeling: Part 7

JOURNAL OF OBJECT TECHNOLOGY

Short notes about OWL 1

Chapter 2 AN INTRODUCTION TO THE OWL WEB ONTOLOGY LANGUAGE 1. INTRODUCTION. Jeff Heflin Lehigh University

Deep integration of Python with Semantic Web technologies

Web Ontology Language: OWL

Development of a formal REA-ontology Representation

Coral: A Metamodel Kernel for Transformation Engines

Today: RDF syntax. + conjunctive queries for OWL. KR4SW Winter 2010 Pascal Hitzler 3

RDF /RDF-S Providing Framework Support to OWL Ontologies

MDA Journal. BPMI and OMG: The BPM Merger A BPT COLUMN. David S. Frankel Lead Standards Architect - Model Driven Systems SAP Labs.

Second OMG Workshop on Web Services Modeling. Easy Development of Scalable Web Services Based on Model-Driven Process Management

Chapter 3 Research Method

Logic and Reasoning in the Semantic Web (part I RDF/RDFS)

An Architecture for Semantic Enterprise Application Integration Standards

LECTURE 09 RDF: SCHEMA - AN INTRODUCTION

Efficient Querying of Web Services Using Ontologies

AT&T Government Solutions, Inc. Lewis Hart & Patrick Emery

An Introduction to the Semantic Web. Jeff Heflin Lehigh University

Web Ontology Language: OWL

IBM Research Report. An MDA-Based System for Ontology Engineering

KDI OWL. Fausto Giunchiglia and Mattia Fumagallli. University of Trento

MDA & Semantic Web Services Extending ODM with Service Semantics

Knowledge Representation for the Semantic Web

Linguaggi Logiche e Tecnologie per la Gestione Semantica dei testi

Main topics: Presenter: Introduction to OWL Protégé, an ontology editor OWL 2 Semantic reasoner Summary TDT OWL

MDA-based Ontology Infrastructure

FOUNDATIONS OF SEMANTIC WEB TECHNOLOGIES

Semantics for and from Information Models Mapping EXPRESS and use of OWL with a UML profile for EXPRESS

Formalising the Semantic Web. (These slides have been written by Axel Polleres, WU Vienna)

Workpackage 15: DBE Business Modeling Language. Deliverable D15.5: BML Editor Final Release

Semantic Technologies and CDISC Standards. Frederik Malfait, Information Architect, IMOS Consulting Scott Bahlavooni, Independent

Semantic Business Process Management Lecture 5 Semantic Technologies I OMG Ontology Definition Metamodel

BLU AGE 2009 Edition Agile Model Transformation

MDA-Based Architecture of a Description Logics Reasoner

Building Blocks of Linked Data

An RDF-based Distributed Expert System

An Alternative CIM Modeling Approach using JSON-LD

AutoRDF - Using OWL as an Object Graph Mapping (OGM) specification language

Spemmet - A Tool for Modeling Software Processes with SPEM

Towards a Data Consistency Modeling and Testing Framework for MOF Defined Languages

Computation Independent Model (CIM): Platform Independent Model (PIM): Platform Specific Model (PSM): Implementation Specific Model (ISM):

Overview of lectures today and Wednesday

Semantic Information Modeling for Federation (SIMF)

Using RDF to Model the Structure and Process of Systems

The Semantic Web. Mansooreh Jalalyazdi

Semantic Web Lecture Part 4. Prof. Do van Thanh

3rd Lecture Languages for information modeling

Ingegneria del Software Corso di Laurea in Informatica per il Management. Introduction to UML

Web Ontology Language: OWL by Grigoris Antoniou Frank van Harmelen

DEVELOPING AN OWL ONTOLOGY FOR E- TOURISM

RDF AND SPARQL. Part III: Semantics of RDF(S) Dresden, August Sebastian Rudolph ICCL Summer School

Semantic Technology. Chris Welty IBM Research

Research on Patent Model Integration Based on Ontology

The Semantic Planetary Data System

Semantic Web Engineering

RDF Schema. Mario Arrigoni Neri

A General Approach to Query the Web of Data

Business Rules in the Semantic Web, are there any or are they different?

Automatic Transformation of Relational Database Schema into OWL Ontologies

Helmi Ben Hmida Hannover University, Germany

Future Directions for SysML v2 INCOSE IW MBSE Workshop January 28, 2017

GraphOnto: OWL-Based Ontology Management and Multimedia Annotation in the DS-MIRF Framework

Contents. G52IWS: The Semantic Web. The Semantic Web. Semantic web elements. Semantic Web technologies. Semantic Web Services

Semantic Web In Depth: Resource Description Framework. Dr Nicholas Gibbins 32/4037

2. RDF Semantic Web Basics Semantic Web

Sequence Diagram Generation with Model Transformation Technology

FOUNDATIONS OF SEMANTIC WEB TECHNOLOGIES

Semantic Web Update W3C RDF, OWL Standards, Development and Applications. Dave Beckett

A Technique for Automatic Construction of Ontology from Existing Database to Facilitate Semantic Web

OSM Lecture (14:45-16:15) Takahira Yamaguchi. OSM Exercise (16:30-18:00) Susumu Tamagawa

METADATA INTERCHANGE IN SERVICE BASED ARCHITECTURE

Chapter 4 Web Ontology Language: OWL

Deep Integration of Scripting Languages and Semantic Web Technologies

Mustafa Jarrar: Lecture Notes on RDF Schema Birzeit University, Version 3. RDFS RDF Schema. Mustafa Jarrar. Birzeit University

Editor s Draft. Outcome of Berlin Meeting ISO/IEC JTC 1/SC32 WG2 N1669 ISO/IEC CD :ED2

Appendix B: The LCA ontology (lca.owl)

Knowledge Representations. How else can we represent knowledge in addition to formal logic?

Transcription:

Metamodels for RDF Schema and OWL Daniel T. Chang Elisa Kendall IBM Silicon Valley Lab Sandpiper Software, Inc. 555 Bailey Ave., San Jose, CA 95141 2053 Grant Road, #162, Los Altos, CA 94024 dtchang@us.ibm.com ekendall@sandsoft.com ABSTRACT This paper presents the working draft MOF (Meta-Object Facility) metamodels for the Resource Description Framework (RDF Schema) and the Web Ontology Language (OWL), two of the six metamodels currently envisioned for the Ontology Definition Metamodel (ODM) standards effort in the Object Management Group (OMG ), which enable model-driven development of RDF vocabularies and OWL ontologies, respectively. We provide insight into some of the design principles used in developing these metamodels, major challenges addressed to date, and the resolution of some of these issues that has influenced the resultant products. We also briefly review ongoing and future work needed to complete the subset of the ODM specific to these representation formalisms and fully support model driven development of RDF vocabularies and OWL ontologies. INTRODUCTION Over the course of the last five years, and more specifically, since the emergence of Semantic Web Activity from the World Wide Web Consortium (W3C) [1], the development of ontologies explicit formal specifications of the concepts in a domain and relations among them [2] has been moving from the research community to early adoption by industry. Increasing evidence of collaborative development of large, standardized controlled vocabularies and ontologies for specific applications and domains, such as in bioinformatics and pharmacogenomics research, is appearing in the literature. Broadly applicable general-purpose ontologies, for example those supporting the Semantic Web Services Initiative [3], are emerging as well. Ontologies are primarily captured in knowledge representation languages developed by the artificial intelligence community. Most of the more commonly-used authoring languages, such as the description logics family of languages [4] or first-order and predicate logic languages, such as Simple Common Logic (SCL) [5] or its predecessor, the Knowledge Interchange Format (KIF) [6], were designed to support machine reasoning. Their text and logic based structure, however, has led to a language syntax that is unfamiliar and awkward for subject matter experts to learn and use effectively, which has been a major hindrance to the development of ontologies. Notably, the recently adopted W3C specifications for the Resource Description Framework (RDF), RDF Schema [7] and the Web Ontology Language (OWL) [8,9] in particular, are somewhat less intimidating to those familiar with XML syntax or constructs used in object-oriented programming, such as classes, properties, and individuals. OWL is an extension of RDF Schema, which is the vocabulary description language for RDF. Both RDF Schema and OWL are key components of the W3C Semantic Web initiative and are likely to gain increasing support in the industry. Having domain expert friendly languages, however, is necessary but not sufficient to promote widespread adoption of these technologies. Current approaches to ontology development are at best, more art than science, and in general, ad hoc. First, the process of ontology development is extremely time consuming and not at all visually intuitive. Any non-trivial ontology represented in OWL, as is, is challenging for domain experts to understand and maintain. Secondly, developing ontologies in isolation of business requirements is of little practical value. Ontology development must become an integral part of the systems analysis and engineering activities of the CIO function. That is, the ontologies that an enterprise develops must form an integral part of that enterprise s information and application infrastructure This paper promotes the use of Model Driven Architecture (MDA ) and related methodologies for ontology development. This is prompted by current trends towards MDA in software engineering and best practices, as a result of the related standards efforts in the OMG, and the availablity of EMF (Eclipse Modeling Framework) as an open source model-driven software development platform. Key standards in the MDA family include the Meta-Object Facility (MOF ) [10] and the Unified Modeling Language (UML ) [11]. UML is an industry-standard, graphical language that is used by software engineers for conceptual modeling. The similarity of UML constructs to constructs used in defining ontologies suggests that UML could be leveraged by the large community of existing practitioners to promote broader use and increasing development of ontologies. UML is well established in many commercial and government software engineering organizations with extensive tool support from both commercial and open source vendors. We believe, therefore, that UML is an excellent candidate notation for the graphical development and maintenance of ontologies. To facilitate the development of tools and methods for MDA-based ontology development, as UML is defined using MOF, what is needed is a MOF based metamodel for OWL. Such a metamodel will enable:! Forward engineering: development of OWL ontologies using MOF based (in particular, UML) modeling tools.! Reverse engineering: leveraging existing OWL ontologies for ontology modeling and UML modeling.! Integrated ontology/software development: making OWL ontology development an integral part of

software development. This paper presents the draft set of MOF metamodels for RDF Schema and OWL that are currently proposed as a part of the Ontology Definition Metamodel (ODM) activity in the OMG, enabling model-driven development of RDF vocabularies and OWL ontologies, respectively. Because of space limitations, we provide only a brief overview of the metamodels here. We present insight into some of the design principles used in developing these metamodels, major challenges addressed to date, and the resolution of some of these issues that has influenced the resultant products. We also briefly review ongoing and future work needed to complete the subset of the ODM specific to these representation formalisms and fully support model driven development of RDF vocabularies and OWL ontologies. DESIGN PRINCIPLES AND MAJOR CHALLENGES Both RDF Schema and OWL are defined using RDF Schema. That is, RDF Schema serves as the meta language that defines itself and OWL. However, to leverage MDA, EMF, and UML technologies, MOF serves as the meta language, or meta-metamodel used to define the metamodels for RDF Schema and OWL. In developing these metamodels, we encountered a number of distinctions between MOF and RDF Schema that have either challenged our ability to leverage MOF for this purpose or have resulted in metamodels that are less than ideal, as discussed below. RDF Schema uses URI references for naming. Definitions specified in RDF documents (class, property, individual) have globally unique names qualified by namespaces, such as rdfs:class, rdf:property, rdfs:subclassof, owl:class, and owl:equivalentclass. MOF, on the other hand, uses package-scoped naming for classes and locally scoped naming for associations. In the current set of metamodels, to clearly indicate what a particular notion, such as a class or an association, describes (i.e., its source), we have elected to use prefixes to denote namespaces. Thus, the entities itemized above are called, respectively: RDFSClass, RDFProperty, RDFSsubClassOf, OWLClass, and OWLequivalentClass. RDF Schema and OWL (and actually most knowledge representation formalisms and methodologies) do not make distinctions between meta-levels. For example, rdfs:class is used to define owl:class (i.e., owl:class is an instance of rdfs:class), but owl:class is also defined as a subclass of rdfs:class. From an MDA perspective, however, these distinctions are extremely important: MOF class, at the M3 level, is used to define M2 level classes, such as RDFSClass and OWLClass. UML does not support representation of classes and objects on the same diagram, which is a frequent requirement in knowledge representation. As a result, we have attempted to respect separation of meta-levels whenever possible in the ODM metamodels, for example, OWLClass is defined as a subclass of RDFSClass, but it is not an instance of RDFSClass. RDF Schema and OWL are based on concepts from formal logic, as mentioned above. They provide unary predicates, i.e., classes and individuals, for representing concepts in a domain and binary predicates, in the form of properties, for representing relations between concepts. Both RDF classes and RDF properties are first-class entities and have globally unique identifiers. MOF, on the other hand, is class based. It provides classes for representing concepts in a domain, attributes for representing characteristics that are common to all instances of a given concept, and associations for representing relations between concepts. MOF classes are first-class entities that may have globally unique identifiers (package scoped). Attributes and associations, however, are not first-class citizens. They have only class-scoped, local names, as mentioned previously. This raised a fundamental question as to how best to represent RDF properties in the metamodels: reified as MOF classes so that they have globally unique identifiers or as MOF associations so that they appear more natural to MOF/UML users. In the current metamodels, we have described predefined RDF properties, e.g., rdfs:subclassof and owl:equivalentclass, as MOF associations in order to make the metamodels easier to understand, simplify the serialized XMI rendering of the metamodels, and for ease of use in MOF and UML tools. Three prefixes (RDF, RDFS and OWL) have been used to denote namespaces, for example RDFSsubClassOf and OWLequivalentClass, to simulate globally unique names, however. Again, the primary goal of this work is to enable model driven development of RDF vocabularies and OWL ontologies. As such, we want the metamodels to be as directly representive of RDF Schema and OWL, respectively, as possible. Therefore, we have kept to a minimum any construct that is not explicitly defined in RDF Schema or OWL. Where we felt such a construct was necessary, for example, Vocabulary / Graph for scoping purposes in the RDF Schema metamodel, we have named these artifacts without any global prefix for further clarification. THE RDF SCHEMA METAMODEL The RDF Schema metamodel uses diagrams to control complexity and promote understanding, as exemplified in Figures 1 and 2. The MOF classes and MOF associations are grouped into seven diagrams:! Classes Contains classes and associations that can be used to define RDF classes and RDF datatypes.! Properties Contains classes and associations that can be used to define RDF properties.! Containers Contains classes and associations that can be used to define RDF containers and their members.! Collections Contains classes and associations that can be used to define RDF collections (i.e., lists) and their members.! Reification Contains classes and associations that can be used to define RDF statements.

RDFSResource namespace : String localname : String uri : String +RDFtype +RDFSsubClassOf RDFSCl ass +RDFSl abel +RDFScomment RDFSDatatype RDFSLiteral lexicalform : String language : String RDFXMLLiteral Figure 1. RDFS Classes Diagram RDFSResource RDFProperty +RDFSdomain RDFSClass +RDFSrange +RDFSsubPropertyOf Figure 2. RDFS Properties Diagram! Utilities Contains classes and associations that can be used to define utility RDF properties.! Vocabulary Contains classes and associations that can be used to define the scope of an RDF vocabulary. Two of the primary diagrams, the RDFS Classes diagram and the RDFS Properties diagram, are shown in Figures 1 and 2, respectively. THE OWL METAMODEL The OWL Metamodel, as illustrated in the OWL Classes Diagram (Fig. 3), also uses diagrams to control complexity and promote understanding.

RDFSClass +OWLcomplementOf OWLThing +OWLoneOf OWLCla ss iscomplete : Boolean +OWLintersectionOf OWLClass +OWLunionOf OWL Restricti on +OWLequivalentClass OWLClass +OWLdisjointWith +OWLversionInfo RDFSLiteral Figure 3. OWL Classes Diagram The MOF classes and MOF associations are grouped into seven diagrams:! Classes Contains classes and associations that can be used to define OWL classes.! Restrictions Contains classes and associations that can be used to define OWL restrictions.! Properties Contains classes and associations that can be used to define OWL properties.! Individuals Contains classes and associations that can be used to define OWL individuals.! Datatypes Contains classes and associations that can be used to define OWL datatypes.! Utilities Contains classes and associations that can be used to define utility OWL classes.! Ontology Contains classes and associations that can be used to define the properties of an OWL ontology. Several of these diagrams are essential to understanding the metamodels and our approach, so we encourage interested researchers and practitioners to review the entire metamodel [12], but to further illustrate what we have done to date, the OWL Properties diagram is shown in Figure 4. FUTURE WORK OWL consists of three increasingly expressive representation formalisms designed for use by specific communities:! OWL Lite supports users primarily concerned with classification hierarchies and simple constraints.! OWL DL supports users who want the maximum expressivity without loss of computational completeness and decidability in certain reasoning systems.! OWL Full supports users who want maximum expressivity and the syntactic freedom of RDF, with less concern for computational guarantees.

RDFProperty Property +OWLversionInfo RDFSLiteral +OWLequivalentProperty +OWLinverseOf OWLObjectProperty OWLDatatypeProperty OWLFunctionalProperty OWLSymmetricProperty OWLTransitiveProperty OWLInverseFunctionalProperty Figure 4. OWL Properties Diagram The OWL metamodel as currently defined is capable of representing any of the three sublanguages of OWL. However, it does not yet include the constraints required to limit OWL Lite and OWL DL per the W3C recommendations. Future work is planned to incorporate such constraints in the submission using OCL. Additionally, we have used the RDFS and OWL metamodels to generate EMF-based Java APIs. These APIs are part of JODM, which includes Java APIs for the full set of ODM metamodels, and consists of six Java packages: org.omg.odm.dl, org.omg.odm.er, org.omg.odm.rdfs, org.omg.odm.owl, org.omg.odm.scl, and org.omg.odm.tm. The org.omg.odm.rdfs package has been used as the basis for developing the EODM tool that is part of the IBM Semantics Toolkit [13]. We plan to make JODM an open source project so that it can be widely utilized. The RDFS and OWL metamodels enable model-driven ontology development using MOF based tools, as illustrated by EODM. However, they may not be sufficient for enabling such development using UML based tools, such as IBM Rational Rose, MagicDraw, ArgoUML, and others. We are currently investigating the need to define UML profiles for RDF Schema and OWL to enable the use of UML notation for modeling purposes and for subsequent generation of corresponding RDF Schema and OWL ontologies. Reference [14] provides additional insight into some of the overall design decisions driving the architecture of the ODM. Depending on the outcome of our research and prototyping activities, such profiles will be included as part of the joint ODM revised submission. We also plan to define mappings from the RDFS and OWL metamodels to RDF Schema and OWL, respectively, and include them in the joint revised submission. ACKNOWLEDGMENT The authors would like to recognize the contribution of Yiming Ye to the initial design of the metamodels for RDF Schema and OWL. They would also like to thank the rest of the ODM submission team for ideas that contributed to the final design of the metamodels: Robert Colomb, Dave Frankel, Patrick Emery, and Lewis Hart. This paper represents the personal perspectives of the authors and does not necessarily represent the common perspectives of the whole team. REFERENCES [1] Tim Berners-Lee and Mark Fischetti, Weaving the Web: the Past, Present and Future of the World Wide Web by Its

Inventor, Orion Business, London, 1999. [2] T. R. Gruber. Towards Principles for the Design of Ontologies Used for Knowledge Sharing, Technical Report KSL-93-04 Knowledge Systems Laboratory, Stanford University, 1993. [3] See http://www.daml.org/services/swsl/ [4] F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi, P.F. Patel-Schneider (editors), The Description Logic Handbook: Theory, Implementation and Applications, Cambridge University Press, January 2003. [5] Michael Genesereth & Richard Fikes, Knowledge Interchange Format, Version 3.0 Reference Manual, KSL Report KSL-92-86, Knowledge Systems Laboratory, Stanford University, June 1992. [6] Harry Delugach, ISO/IEC WD 24707 Information technology Common Logic (CL) A Framework for a Family of Logic-Based Languages, Pacific Northwest National Laboratory, Chantilly, VA, 7 June 2004. [7] RDF Vocabulary Description Language 1.0: RDF Schema. W3C Recommendation 10 February 2004. Latest version is available at http://www.w3.org/tr/rdf-schema/. [8] OWL Web Ontology Language Reference. W3C Recommendation 10 February 2004. Latest version is available at http://www.w3.org/tr/owl-ref/. [9] OWL Web Ontology Language Semantics and Abstract Syntax. W3C Recommendation 10 February 2004. Latest version is available at http://www.w3.org/tr/owl-semantics/. [10] Unified Modeling Language (UML ) Infrastructure Specification, Version 2.0, Object Management Group, Inc., Needham, MA, December 2003. [11] Meta-Object Facility (MOF ) Specification, Version 2.0, Object Management Group, Inc., Needham, MA, August 2003. [12] See http://codip.grci.com/odm/draft/. [13] Guotong Xie, Shixia Liu, Zhuo Zhang, Li Ma, Yue Pan, Li Zhang, Zhong Su, and Li Qin Shen, SemanticWare: An EMF-Compatible RDF Infrastructure, in Proceedings, the 8 th International IEEE EDOC Conference, 1st International Workshop on the Model Driven Semantic Web (MDSW 2004), Monterey, CA, September 21, 2004. [14] Daniel T. Chang and Elisa Kendall, Major Influences on the Design of ODM, in Proceedings, the 8 th International IEEE EDOC Conference, 1st International Workshop on the Model Driven Semantic Web (MDSW 2004), Monterey, CA, September 21, 2004.