Ontology Development Kenneth Baclawski Northeastern University Harvard Medical School.

Slides:



Advertisements
Similar presentations
Ontology-Based Computing Kenneth Baclawski Northeastern University and Jarg.
Advertisements

Major Influences on the Design of ODM Dan Chang (IBM) Elisa Kendall (Sandpiper) MDSW 2004.
Dr. Leo Obrst MITRE Information Semantics Information Discovery & Understanding Command & Control Center February 6, 2014February 6, 2014February 6, 2014.
Profiles Construction Eclipse ECESIS Project Construction of Complex UML Profiles UPM ETSI Telecomunicación Ciudad Universitaria s/n Madrid 28040,
Using DAML format for representation and integration of complex gene networks: implications in novel drug discovery K. Baclawski Northeastern University.
Schema Matching and Query Rewriting in Ontology-based Data Integration Zdeňka Linková ICS AS CR Advisor: Július Štuller.
Of 27 lecture 7: owl - introduction. of 27 ece 627, winter ‘132 OWL a glimpse OWL – Web Ontology Language describes classes, properties and relations.
Ontology Notes are from:
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 8 The Enhanced Entity- Relationship (EER) Model.
UML CASE Tool. ABSTRACT Domain analysis enables identifying families of applications and capturing their terminology in order to assist and guide system.
Semantics For the Semantic Web: The Implicit, the Formal and The Powerful Amit Sheth, Cartic Ramakrishnan, Christopher Thomas CS751 Spring 2005 Presenter:
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment Natalya F. Noy and Mark A. Musen.
The RDF meta model: a closer look Basic ideas of the RDF Resource instance descriptions in the RDF format Application-specific RDF schemas Limitations.
1 Conceptual Modeling of Topic Maps with ORM Versus UML Are D. Gulbrandsen The XML group, Center for Information Technology Services, University of Oslo,
The Enhanced Entity- Relationship (EER) Model
OIL: An Ontology Infrastructure for the Semantic Web D. Fensel, F. van Harmelen, I. Horrocks, D. L. McGuinness, P. F. Patel-Schneider Presenter: Cristina.
A Really Brief Crash Course in Semantic Web Technologies Rocky Dunlap Spencer Rugaber Georgia Tech.
Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA.
Vocabulary Services “Huuh - what is it good for…” (in WDTS anyway…) 4 th September 2009 Jonathan Yu CSIRO Land and Water.
Katanosh Morovat.   This concept is a formal approach for identifying the rules that encapsulate the structure, constraint, and control of the operation.
Slide 1 Wolfram Höpken RMSIG Reference Model Special Interest Group Second RMSIG Workshop Methodology and Process Wolfram Höpken.
 Copyright 2005 Digital Enterprise Research Institute. All rights reserved. Towards Translating between XML and WSML based on mappings between.
©Ian Sommerville 2000 Software Engineering, 6th edition. Chapter 7 Slide 1 System models l Abstract descriptions of systems whose requirements are being.
1 CS 456 Software Engineering. 2 Contents 3 Chapter 1: Introduction.
Extending UML to Support Ontology Engineering Kenneth Baclawski and Mieczylaw K. Kokar Northeastern University Paul A. Kogut, William S. Holmes III and.
INF 384 C, Spring 2009 Ontologies Knowledge representation to support computer reasoning.
9/14/2012ISC329 Isabelle Bichindaritz1 Database System Life Cycle.
Introduction to MDA (Model Driven Architecture) CYT.
RDF and OWL Developing Semantic Web Services by H. Peter Alesso and Craig F. Smith CMPT 455/826 - Week 6, Day Sept-Dec 2009 – w6d21.
Copyright 2002 Prentice-Hall, Inc. Modern Systems Analysis and Design Third Edition Jeffrey A. Hoffer Joey F. George Joseph S. Valacich Chapter 20 Object-Oriented.
Emerging Semantic Web Commercialization Opportunities Ken Baclawski Northeastern University.
Of 33 lecture 10: ontology – evolution. of 33 ece 720, winter ‘122 ontology evolution introduction - ontologies enable knowledge to be made explicit and.
1 Ontology-based Semantic Annotatoin of Process Template for Reuse Yun Lin, Darijus Strasunskas Depart. Of Computer and Information Science Norwegian Univ.
Metadata. Generally speaking, metadata are data and information that describe and model data and information For example, a database schema is the metadata.
Chapter 7 System models.
Ontology Summit2007 Survey Response Analysis Ken Baclawski Northeastern University.
Knowledge Representation of Statistic Domain For CBR Application Supervisor : Dr. Aslina Saad Dr. Mashitoh Hashim PM Dr. Nor Hasbiah Ubaidullah.
Database Systems: Enhanced Entity-Relationship Modeling Dr. Taysir Hassan Abdel Hamid.
1 Capturing Requirements As Use Cases To be discussed –Artifacts created in the requirements workflow –Workers participating in the requirements workflow.
Using Meta-Model-Driven Views to Address Scalability in i* Models Jane You Department of Computer Science University of Toronto.
Ontology-Based Computing Kenneth Baclawski Northeastern University and Jarg.
Design Model Lecture p6 T120B pavasario sem.
Object-Oriented Modeling: Static Models. Object-Oriented Modeling Model the system as interacting objects Model the system as interacting objects Match.
Metadata Common Vocabulary a journey from a glossary to an ontology of statistical metadata, and back Sérgio Bacelar
Of 33 lecture 1: introduction. of 33 the semantic web vision today’s web (1) web content – for human consumption (no structural information) people search.
Mining the Biomedical Research Literature Ken Baclawski.
The RDF meta model Basic ideas of the RDF Resource instance descriptions in the RDF format Application-specific RDF schemas Limitations of XML compared.
WIGOS Data model – standards introduction.
Issues in Ontology-based Information integration By Zhan Cui, Dean Jones and Paul O’Brien.
Topic Maps introduction Peter-Paul Kruijsen CTO, Morpheus software ISOC seminar, april 5 th 2005.
Extending the MDR for Semantic Web November 20, 2008 SC32/WG32 Interim Meeting Vilamoura, Portugal - Procedure for the Specification of Web Ontology -
Object-Oriented Parsing and Transformation Kenneth Baclawski Northeastern University Scott A. DeLoach Air Force Institute of Technology Mieczyslaw Kokar.
WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WP2: Tools Raphael Volz Universität.
Enable Semantic Interoperability for Decision Support and Risk Management Presented by Dr. David Li Key Contributors: Dr. Ruixin Yang and Dr. John Qu.
Ontologies Reasoning Components Agents Simulations An Overview of Model-Driven Engineering and Architecture Jacques Robin.
Semantic Interoperability in GIS N. L. Sarda Suman Somavarapu.
Data Models. 2 The Importance of Data Models Data models –Relatively simple representations, usually graphical, of complex real-world data structures.
Sheet 1MDAFA2004 Linköping, June 2004 A Language for Model Transformations in the MOF Architecture Ivan Kurtev, Klaas van den Berg University of Twente,
Of 24 lecture 11: ontology – mediation, merging & aligning.
The Semantic Web By: Maulik Parikh.
Object Management Group Information Management Metamodel
SysML v2 Formalism: Requirements & Benefits
Lecture #11: Ontology Engineering Dr. Bhavani Thuraisingham
Web Ontology Language for Service (OWL-S)
Associative Query Answering via Query Feature Similarity
ece 720 intelligent web: ontology and beyond
Extending UML to Support Ontology Engineering
ece 627 intelligent web: ontology and beyond
Piotr Kaminski University of Victoria September 24th, 2002
Ontology-Based Approaches to Data Integration
Presentation transcript:

Ontology Development Kenneth Baclawski Northeastern University Harvard Medical School

Outline §Background on ontologies §Ontology development phases l Requirements and Analysis l Design and Implementation l Testing and Validation l Maintenance §Comparison of ontologies and software l Classes l Relationships l Logic §Conclusion

Ontologies §Ontology: What exists in a domain and how they relate with each other. §Formal ontology: Formal treatment of the concepts and relationships in a domain. §Simple Example: l Employees work for Companies l Employees report to Employees

Statements George is an employee. An object is an instance of the Employee class. George works for Sony. George reports to Adam. Fred works for a company. Fred must report to a another employee. Fred reports to two other employees. George says that Fred works for Toyota. An object in the Employee class is linked with an object in the Company class via the works_for relationship. An object in the Employee class is linked with another object in the same class via the reports_to relationship.

Purposes of Ontologies §Basis for communication l Between people (may be informal) l Between agents (formal ontologies) §Applications l Representing and storing data (e.g., DB schema) l Knowledge sharing within and between domains l Search and retrieval l Software development l Classification and organization of data resources l Establishing contracts l Policy enforcement

Criteria for Introducing Ontologies §Large amounts of data l Data available on the Web l Data acquired or generated by new techniques §Complex data structures l Inheritance, containment and other hierarchies l Many relationships §Diverse sources l Many legacy systems l Sources on the Web using different formats §Requirement for formal proofs l Contracts and policy enforcement

Ontology Development Today §The ideal is for the tools to be based on methodologies and processes. §The reality is the reverse: methodologies are based on the tools. §Opportunity: The lack of good ontology development processes and methodologies §Thesis: Given that formal ontologies are a form of software, software development methodologies can be adapted to serve ontology development.

Classification of Ontology Languages §Logical languages l First order predicate logic l Rule based logic l Description logic §Frame based languages l Similar to relational databases §Graph based languages l Semantic networks l Analogy with the Web is rationale for the Semantic Web

Some Ontology Languages §Established languages l Knowledge Interchange Format (KIF) l XML Schema (XSD) l Resource Description Framework (RDF) l XML Topic Maps (XTM) §Emerging languages l Common Logic l Web Ontology Languages (OWL) l Ontology Definition Metamodel (ODM)

Ontology Development Phases §Requirements and Analysis §Design and Implementation §Testing and Validation §Maintenance

Requirements and Analysis §Least understood of all phases §Direct involvement by stakeholders is essential, but how? §Specifying the scope is important, but not all languages support it. §Point of view is also relevant. §These phases offer significant opportunities for new methodologies and processes.

Design and Implementation: Patterns and Reuse §Design pattern: Use known patterns §Metaphor: Transform another ontology §Composition: Transform and combine many smaller ontologies Common Features Ontology1Ontology2 Combined Ontology

Boolean Logic Geographic OntologyFuzzy Logic Fuzzy Geographic Ontology Example of ontology composition The arrows are theory morphisms in the category of theories. The composition is the colimit: the theories are combined such that the common features are equivalent. The composition not only allows one to express fuzzy geographic statements but also to propagate uncertainty from base facts (observations) to derived facts via rules.

Design and Implementation: Refactoring §Move methods from one class to another (for example, from subclasses to superclasses). §Reification and unreification: changing relationships into classes or vice versa. §Metalevel shifting (for example, reflection) §Refactoring adjusts ontological commitment. §Refactoring is useful at the design, implementation and maintenance phases.

Example of Refactoring

Example of Reification

Testing and Validation §Validation of requirements §Consistency checking

Comparison of ontologies and software §Classes l Sets versus templates l Behavior versus set-theory §Properties l Aspects §Logic l Open versus closed

Class: Set or Template §Object-oriented classes are templates. They allow one to construct objects with specified features. §Formal ontological classes are sets which can be defined in terms of other classes, attributes and associations.

Derived class example §When the age of a person is updated, membership in the Teenager class may also be changed.  When testing for membership in a class, one should use isCompatibleWith or isConsistentWith rather than instanceof.

Class: Set-theory or Behavior

Properties §Property is a general term for attributes and associations. §Are properties first class or second class? §First class properties are an example of an aspect: a feature that cuts across class boundaries. §First class properties are part of UML2.0.

Logic: Open versus Closed §Open (monotonic) logic gives different answers to queries than a closed logic. §Suppose that Fred is just an employee: l Closed world: violates constraint l Open world: Fred works for a company, but the company is not known.

Logic: Open versus Closed §Suppose that Fred works for both Sony and IBM: l Closed world: violates constraint l Open world: Sony and IBM are the same company!

Statements §Fred works for a company. l The Fred object is an instance of the class of employees who work for at least one company. §Fred reports to two other employees. l The Fred object is an instance of the class of employees who report to exactly two employees. l The Fred object is an instance of the class of employees who do not report to themselves.

Statements §Fred must report to a another employee. l The Fred object is an instance of the class of employees who report to at least one employee. l The Fred object is an instance of the class of employees who do not report to themselves. §George says that Fred works for Toyota. l Homework assignment. l Hint: Use reification.

Conclusion §There is a noteworthy lack of methodologies and process models for ontology development. §Software development methodologies and processes could be adapted for ontologies. §However, many challenges remain to be solved.

Some of my efforts toward adapting software development for ontologies §Extend UML to support ontologies l The UML has approved some of my suggestions §Direct support for ontology development by CASE tools l The OMG has issued an RFP l Four initial submissions have been presented. l Use cases are being developed §Transformations between formal languages l The OMG has issued an RFP l Six submissions are at the revised submission stage. l Several products already exist