Verisözlüğü (Alt) Çalışma Grubu

Bilgilendirme Toplantısı

Gökhan Özkan

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Agenda

Neden buradayız ve bu toplantıyı yapıyoruz?

Birlikte Çalışabilirlik ve Seviyeleri

Tanımlar

Anlam Düzeyinde Birlikte Çalışabilirlik

Örnekler ve Gelişmeler

Türkiye Yol Haritası Tartışması

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Neden Buradayız?

Ülkemizdeki e-devlet girişimi kritik bir eşiğe yaklaşmakta

Momentum arttıkça, bu kütleyi aynı yöne ve aynı hedefe doğru yönlendirmek güçleşmekte

Kaynakların etkin kullanılması için planlama ve hazırlık önemli bir unsur haline gelmekte

Dönüşümle birlikte kurumlar arası ilişkiler ve ilişki biçimleri değişmekte

Genel Sağlık SigortasıAdalet Bakanlığı UYAP

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Neden Buradayız? (2)

DPT Bilgi Toplumu Dairesi bu gelişmeleri yönlendirebilmek için ortak akıla ve işgücüne ihtiyaç duymakta

Birbirimizi anlamak ve kurumlarımızın dışındaki dünyayı da hissedebilmek için anlamsal düzlemde mekanizmaları oluşturacak hareketi başlatmak istemekteyiz

Kurumlar arasındaki sayısal eşitsizlik kavramının engellenmesi ve hareketin topyekün olarak devam ettirilebilmesini temin etmek için

Kurumlarımızı ve vatandaşlarımızı birbirine bağlayacak bu (elektronik) çimentonun karılması için buradayız

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Interoperability

Enterprise

Object

System

Application

Component

0% 100%

6 Levels of Interoperabilit

y

3 Kinds of Integration

Interoperability Scale

Our interest lies here

Community

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Layers of Interoperability (NATO-Mil)

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Interoperability Levels

Technical Interoperability is a level to guarantee right symbols delivered correctly to intended recipients (TCP/IP)

Data interoperability level concerned wit meaning of the symbols, which are delivered to the recepient; at this level mutual understanding is needed between the sender and the receiver on the presentation, encoding and their sytactic formation

Information theory tells that, information delivered to a recepient does not depend on symbols used for encoding or communication channel. But, information density depends on communication medium and selected symbols

Semantic interoperability is needed to communicate/share knowledge. Terms either refer entities that can be sensed or abstract concepts in a domain of knowledge. If compared to natural languages, concepts, grammatical and inference rules should also be in the semantic model

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Concepts To Discuss

English

Vocabulary

Controlled Vocabulary

Thesaurus

Taxonomy

Formal Ontology

Metamodel

Data Dictionary

Türkçe

Terimler Sözlüğü (dağarcık)

Kontrollü Dağarcık

Eşanlamlılar Listesi

Taksonomi

Formal Ontoloji

Metamodel

Veri Sözlüğü

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Definitions

Vocabulary : Listed terms, explicitly defined under a domain of knowledge

Controlled Vocabulary : A vocabulary, which has a registration authority to control terms in the vocabulary and their explicit meanings; two rules enforced

If the same term is commonly used to mean different concepts in different contexts, then its name is explicitly qualified to resolve ambiguityIf multiple terms are used to mean the same thing, one of the terms is identified as the preferred term in the CV and the other terms are listed as synonyms or aliases

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Definitions (2)

Thesaurus : Two definitionsA networked collection of controlled vocabulary terms. This means that a thesaurus uses associative relationships in addition to parent-child relationships. The expressiveness of the associative relationships in a thesaurus varies and can be as simple as “related to term”.A list of words showing similarities, differences, dependencies and other relationships to each other

Taxonomy : A collection of controlled vocabulary terms organized into a hierarchical structure. Each term in taxonomy is in one or more parent-child relationships to other terms in the taxonomy. There may be different types of parent-child relationships in a taxonomy (whole-part, genus-species, type-instance). Taxonomies may allow poly-hierarchy which means that a term can have multiple parents.

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Definitions (3)

Formal Ontology : A formal ontology is a controlled vocabulary expressed in an ontology representation language. This language has a grammer for using vocabulary terms to express something meaningful within a specified domain of interest. The grammer contains formal contraints (specifies what it means to be a well-formed statement, assertion, query, etc) on how terms in the ontology’s controlledvocabulary can be used together.

“Represent formal and consensual specifications of conceptualizations, which provide a shared and commonunderstanding of a domain as data and information machine-processable semantics, which can be communicated among agents(organizations, individuals, and software)” [Fensel, 2001]

Meta Model :An explicit model of the constructs and rules needed to build specific models within a domain of interest. A valid metamodel is an ontology, but not all ontologies are modeled explicitly as metamodels. A metamodel can be viewed from three different perspectives

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Definitions (4)

Data Dictionary : The metadata layer of (usually) relational databases which shows the entity-relation diagrams, triggers, stored procedures, etc. It can be defined as an ontology but it lacks the context and is not open. It is specific to database vendor.

Veri Sözlüğü :Biz bu çalışma grubu için verisözlüğü kelimesini daha önce vermiş olduğumuz tüm tanımlamaların kapsayıcısı olarak kullanıyoruz. Başka bir tanım ya da isim buluncaya kadar da böyle devam edecektir. Bu sözcüğün anlamında bir kayma manasına gelmektedir.

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Formal Taxonomy

OWL Listing:<?xml version="1.0"?> <rdf:RDF

xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:daml="http://www.daml.org/2001/03/daml+oil#" xmlns="http://www.owl-ontologies.com/unnamed.owl#" xmlns:dc="http://purl.org/dc/elements/1.1/" xml:base="http://www.owl-ontologies.com/unnamed.owl"> <owl:Ontology rdf:about=""/> <owl:Class rdf:ID="Transportation"/> <owl:Class rdf:ID="AirVehicle"> <rdfs:subClassOfrdf:resource="#Transportation"/> </owl:Class> <owl:Class rdf:about="#GroundVehicle"> <rdfs:subClassOfrdf:resource="#Transportation"/> </owl:Class> <owl:Class rdf:about="#Automobile"> <rdfs:subClassOf> <owl:Class rdf:ID="GroundVehicle"/> </rdfs:subClassOf> Etc.

Transportation Class Hierarchy

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Health Domains Taxonomy

Access to CareFocuses on the access to appropriate care

Population Health and Consumer SafetyAssesses health indicators and consumer products as a means to protect and promote the health of the general population

Health Care AdministrationAssures that federal health care resources are expended effectively to ensure quality, safety, and efficiency

Health Care Delivery ServicesProvides and supports the delivery of health care to its beneficiaries

Health Care Research and Practitioner EducationFosters advancements in health discovery and knowledge

Source: Introduction to the Federal Health Architecture Development Methodology, Briefing to the FHA APRG, February 10, 2005.

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Basic Components of Ontology

Concept: Belli bir Bilgi/Etki Alanındaki nesnelerin içerdikleri özelliklerle birlikte organize olmuş halidir. Genellikle taksonomiler içerisinde düzenlenirler.Value: Bir konseptin bilinen bir elemanını tanımlar, gösterirRelations: Bir Bilgi Alanı içerisinde yer alan konseptler arasındaki ilişkileri tarif ederFunction/Method: Bir konseptin belli bir değeri için uygulanabilecek bir metodu tarif eder.Axiom: Sonucu her zaman doğru olan tümceler.

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Classification of Ontologies

Degree of formality: The simpler taxonomical types are called informal ontologies, and generally exist as a list of terms, arranged in hierarchicalrelationships. If natural language definitions are provided for each term in the hierarchy, they are called terminological ontologies. When the relationships between each term have been explicitly stated in formal logic or as axioms that can be processed programmatically, we are dealing with formal ontologies.

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Classification of Ontologies (2)

Granularity: In addition to their degree of formality, ontologies are typically classed according to granularity, from the general to the specific. The most general ontologies, or top level ontologies, deal with concepts not specific to any one domain. These might deal with time, for example, providing a framework for concepts related to the measurement of time. Domain ontologies are those related to a specific domain of knowledge.

Also included in the granularity scale are application ontologies, which essentially combine the definitions provided within specific domain ontology with a set of functional rules for performing a process or task upon the classes and individual terms in the domain ontology. Related to the application ontology is the task ontology, which defines specific tasks and their sequences or procedures.

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Classification of Ontologies (3)

Finally, the type of ontology, which is derived from the common elements occurring across multiple ontologies, is called Meta ontology, or is alternately referred to as a core ontology or generic ontology.

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Categories of Ontologies

M o st G e n e ra l T h in g

P ro c es s L o c a tio n

G e o g ra p h ic A re a o f In te res t

A irsp a ce T arg e t A re a o f In te res t

U p p e rO n to lo g y

M id -L e ve lO n to lo g y

D o m a inO n to lo g y

M o st G e n e ra l T h in g

P ro c es s L o c a tio n

G e o g ra p h ic A re a o f In te res t

A irsp a ce T arg e t A re a o f In te res t

U p p e rO n to lo g y

M id -L e ve lO n to lo g y

D o m a inO n to lo g y

SUMO

HL7 RIM

FEA-RMO*

EONSNOMED CTLOINC

Examples

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Shared Ontologies

Merged ontologies encompass cases of partial compatibility, where some sections or terms of the source ontologies have been unified, or cases of unification, in which each class and term from the source ontologies have been forced to become fully compatible with the others. In both cases the resulting merged ontologies contain distortions of the structural elements of the source ontologies and are no longer functional according to their original hierarchical arrangements.

Integrated ontologies are those in which each class and individual term of the source ontologies have been preserved intact, but are rearranged into a new all-encompassing hierarchy along with some additional concepts and relationships to create a functional whole. With true integration, the original terms are not changed or distorted and are useable as separate components or as integrated members of the new ontology.

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Evolution of ICT

Age of Programs

Age of Proprietary

Data

Age of OpenData

Age of Open

Metadata

Age of SemanticModels

Program-Data

GIGO/minis/micros www / Netscape Web services OWL

Text, Office DocsDatabases

(proprietary schema)

HTML,XML

(open schema)

Namespaces,Taxonomies,

RDF

Ontologies&

Inference

1945 -1970 2000 - 20031994 - 20001970 - 1994 2003 -

ProceduralProgramming

Object-OrientedProgramming

Model-DrivenProgramming

“Data is lesslessimportant

than code”

“Data is asasimportantas code”

“Data is moremoreimportant

than code”

Michael Daconta, Creating Relevance and Reuse with Targeted Semantics, XML 2004 Conference Keynote, November 16, 2004.

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The Semantic Technology “Layer Cake”

Source: Dieter Fensel

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Semantic Technology Landscape

Source: Tim-Berner Lee, “Standards, Semantics and Survival,“http://www.w3.org/2003/Talks/01-siia-tbl/Overview.html

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Business Reference Model Taxonomy

Four Business Areas-one of which is:Services to Citizens, which has

19 Lines of Business-one of which is:Health, which has

5 Topics:Health Care ServicesIllness PreventionImmunization ManagementPublic Health MonitoringConsumer Health and Safety

"The Business Reference Model is a function-driven framework for describing the business operations of the Federal Government independent of the agencies that perform them.“ Federal Enterprise Architecture Program Management Office. 2004.

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FEA Reference Model Ontology FEA-RMO*

The purpose of FEA-RMO is to:Define an ontology based on FEA reference models (PRM, BRM, SRM, TRM, and DRM),Develop a common vocabulary, or lexicon, from the FEA reference models,Support execution, validation, and inference based on FEA reference models,Support e-Government initiativeSupport OMB/AIC partnership in AIC Task 1 & AIC Task 4 by providing lessons learned and an ontology.

Source: GSA FEA Reference Model Ontology: A Domain Specific Parsimonious Ontology, Rick Murphy, Enterprise Architect, Office of the CIO, GSA, January 18, 2005.

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Semantic WEB – Vision

The Semantic Web:–Bilginin/Verinin Alet-İşleyebilir ve Alet-Anlayabilir Semantik kazandığı yeni kuşak WWW yaklaşımıdır. –Web Sayfalarının anlamsal içeriğine yapısal bir yaklaşım getirmektedir.–Yeni bir WEB olmaktan çok, varolan WEB yapısında veriye bilgi olmak yolunda iyi tanımlanmış anlam kazandırılması çabasıdır.

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Semantic GOV Project

Project Headlines

PA domain modelingPA service ontology, as a specialization of a generic ontology for Web Services (WSMO)Goal/need-to-service mediationSemantic Services RepositoriesArchitecture, methodology, and implementation roadmap to design and develop National and Pan-European eGovernmentServices with the use of Semantic Web ServicesSemantic mediation amongst divergent administrative systemsAutomatic and intelligent composition of Web Services, and Distributed Business Process Management

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Semantic GOV Architectural Approach (1)

National Plain

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Semantic GOV Architectural Approach (2)

EU Plain

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Semantic GOV Architectural Approach (3)

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E-Government Architecture

Single access point for citizens

Tools for collecting information

Autonomous Public Administrations

Keep their internal processes and legacy systems intact

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Semantic Interoperability Among Agencies

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WebDG Model as an Example

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Thank You

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