25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU1 Developing Ontologies for Knowledge Management Atilla ELÇİ Dept. of Computer Engineering Eastern Mediterranean University

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU2 Knowledge Management Topics  Motivation  Terms & Definitions  Roles of ontologies  PROTON ontology as bases for KM / SemWeb Apps

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU3 Motivation  Knowledge Representation (KR): = A world view: Building models of a domain/problem which allow for automatic reasoning and interpretation. => Formal semantics (Ontology!) => Machine-interpretable meaning  Semantic repository: Storage, querying, and management of structured data  DBMS vs Ontology-based O-B provides depth of meaning not available through DBMS

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU4 Terminology: KM views  What Is Knowledge Management by the The Knowledge Management Forum (KMForum): What Is Knowledge ManagementThe Knowledge Management Forum (KMForum)  Read through these personal views on K & KM  Note the diversity of views & interests  Contrast & cross-check definitions of some viewers.

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU5 Terminology  Dublin Core Metadata Initiative (DCMI, DC): interoperable online metadata standards  Dataset: a set of structured data (list, table, DB, etc.) useful for direct software processing  Ontology: = Paradigm for KR in AI. Conceptual schemata Formal ontology as logical formalism as in OWL Schemata or ‘inteligent’ views over information resources:  For indexing, querying, and referencing non-ontological datasets  For DB, Document Mngt Sys, Catalog, OLAP,

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU6 Terminology (continued)  Ontology classification based on generality of conceptualization: Upper-level ontology: A general model suitable for large variety of tasks, domains, and application areas. Can be used to line up independently developed ontologies if linked to it. Domain ontology: For ‘specific’ domain of interest App / Task ontology: For a specific range of applications / tasks.  Knowledge base (KB): A dataset with formal semantics and knowledge representation allowing automatic inference.  Ontology: O= where: C: is the set of classes R: is the set of relations among the classes I: is the set of instances from the domain. Instances belong to classes A: is the set of axioms (say, business rules).

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU7 Terminology (continued)  Ref ontology definition as O-grammar, the issue of what is instance what is schema definition may not always easily resolved.  Data qualia: A data quale is an orthogonal quality of data that may be used for independent classification: Semantics: whether it is formally represented Structure: if the data is formally structured Schema: data that determines shape and/or meaning of ontology data.  Sorts of data (“_” stands for ‘any value’ not determined): Data: (_,_,_), ie. Any sort of collection of data  Dataset: (_,structured,_)  Knowledge Base: (semantic,structured,_)  Ontology: (semantic,structured,schema)  Non-semantic schemata: (nonsemantic,structured,schema)  Database: (nonsemantic,structured,schema)  Mixed datasets: (_,structured,schema&non-schema)  Content: (_,non-structured,_) Metadata: data on data, annotation,... How to represent in (?,?,?)? Semi-structured data:

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU8 Terminology (continued)  Sorts of data (continued): Semi-structured data:  KR/NLP  Docs containing free text fragments in structured according to some schema  DB  Data of non-relational data model. Ref. Fig Structured vs semantic positioning of various sorts of data.

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU9 Roles of Ontologies  Ontology as Database Schema: May not contain instance data. Such as RDBMS schema.  Ontology as Topic Hierarchy: Classification for various purposes:  DCMI and library classification  Yahoo & DMoz taxonomies for Web data Yahoo DMoz  See Section 4 in this for depth of Yahoo! Directory.Section 4 in this  Compare Topic-Ontology versus Schema-Ontology (Sect. 7.5)  Ontology as Enterprise Resource Model: Ref.: Ontolog Database & Ontology Mini-Series.Database & Ontology

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU10 Mapping & Querying Disparate Knowledge Bases  Self study: Davies §6.3

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU11 PROTON (PROTo ONtology) Ontology  A light-weight uppper-level ontology to serve as model bases for information science community for, for example: Seed for ontology generation Automatic entity recognition & information extraction Metadata generation / semantic annotation.  Design Rationale: For usage in KM & SemWeb appls Light-weight: for being unrestrictive Prefers not to deal with time & space Low-cost of adoption & maintenance Scalable reasoning

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU12 PROTON (contiuned) Consists of ~300 classes & 100 properties for: Semantic annotation Indexing, and retrieval.  Design principles: Domain independence Light-weight logical definitions Alignment with popular metadata standards Good collection of named entity types (people, organizations, locations, numbers, dates, addresses.  Structure: In OWL Lite In four modules: System, Top, Upper, and Knowledge Management (KM) Organized á la DILIGENT Methodology,

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU13 PROTON (contiuned)  Scope: Developed in the SEKT Project through sampling of a corpus of general news.SEKT Project General entity types appearing commonly (Person, Location, Organization, Money, Date,...) are in PROTON Top. KM aspects stems from:  KIMO of KIM ProjectKIM Project  OpenCyc OpenCyc  Wordnet Wordnet  DOLCE DOLCE  EuroWordnet Voluntary compliance with:  Dublin Core  Automatic Content Extraction annotation types  Alexandria Digital Library Feature Type Thesaurus Alexandria Digital Library  Future compliance with: FOAF and other popular standars & ontologies.FOAF

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU14 PROTON (contiuned)  Architecture: Site at Semanticweb.org Organized in three levels: Basic, Top, Upper In four modules:  System (basic; protons:...): application ontology meant for use by ontology-based software  Top (top; protont:...): abstractions  Upper (upper; protonu:...): specific cases  KM (upper; protonkm:...): specific cases

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU15 PROTON (contiuned)  KM module: for application-specific extension of PROTON: Information Space:collection of themed info resources Software Agent: specialized Agent User: User and UserProfile Profile User Profile Mention: name droppings, references to (private) instances Weighted Term: relates objects to numbers Device: references to user devices.

Organizations  The Knowledge Management Forum (KMForum) The Knowledge Management Forum (KMForum) Virtual community of practice focused on furthering fundamental theories, methods and practices. Features archives and news. What Is Knowledge Management  KM Forum KM Forum Boston Knowledge Management Forum: A Community of Practice: Learning and Working in the Knowledge Management Community  KnowledgeBoard KnowledgeBoard Forum to establish a community and to support and identify commonality in terminology, application and implementation. Features news, workshops, a library,... 25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU16

Conferences  Knowledge Representation Ontology Workshop (KROW 2008).KROW 2008  Eleventh International Conference on Principles of Knowledge Representation and Reasoning (KR 2008),KR 2008 Sydney, Australia, September , /04/'07 updated 15/04708CmpE 588 Spring 2008 EMU17

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU18 Commercial Conferences  Knowledge Base Publishing course series of the Montague Institute includes articles: Knowledge Base Publishing course series Introduction to Knowledge Base Publishing Taxonomies, search & Sharepoint Metadata and search Integrating taxonomies Information modeling and metadata management  See also Roundtables, for example the following:Roundtables Benchmarking Sharepoint for KM (December 12, 2007) Benchmarking Sharepoint for KM Six weeks to the Semantic Web (November 7, 2007) Six weeks to the Semantic Web Integrating folksonomies with Google (October 17, 2007) Integrating folksonomies with Google Migrating metadata to the Semantic Web (September 5, 2007) Migrating metadata to the Semantic Web

25/04/'07 updated 15/04708CmpE 588 Spring 2008 EMU19 References  John Davies, Rudi Studer, Paul Warren (Editors): Semantic Web Technologies: Trends and Research in Ontology-based Systems, John Wiley & Sons (July 11, 2006). ISBN: Ch. 7.: pp  W3C Semantic Web Tools Wiki page:Semantic Web Tools Check...