CopyRight @PavithraKenjige, PK Technologies 1 Usage of Medical Ontology in EA By Pavithra Kenjige PK...

CopyRight @PavithraKenjige, PK Technologies

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Usage of Medical Ontology in EA

By Pavithra KenjigePK TechnologiesAugust 4, 2010


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Usage of Standard Based ontology

Usage of Standard based Ontology to achieve interoperability and system integration and Enterprise Architecture in medical domain.


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Overview

What is Ontology Types of Ontologies, and methodologies Ontology Representation languages Example of Medical Ontologies Enterprise Architecture and Ontology development Standards based Ontology Integration and Interoperability of Medical systems

– Problem– Ontology as solution

Ontology usage in SOA & Semantic Web Benefits of Ontology References


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What is Ontology

Is derived from the two Greek words (ontos) meaning “to be” and (logos) meaning “word.” Ontology is the science or study of being.

In philosophy, ontology refers to the study of nature of being and existence

In Bio medical & Ontolog Forums an Ontology is described as a controlled vocabulary of well defined terms, with specified relationships between them, capable of interpreted by both humans and computers..

Ontology is used to develop standardized, well defined terms and concepts, that support syntactic and semantic interoperability across domains

– For a given Enterprise, and systems that support the domain Knowledge Information Data

– From Information Systems to humans Data Information Knowledge Wisdom


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Ontology, Terminology & Lexical resources

Ontology: The study of what exists and how it can be formally described and axiomatized.

Taxonomy: A classification of the technical terms used in any branch of science, engineering, business, and the arts.

Lexical resource: A dictionary, thesaurus, grammar, or other representation of the vocabulary, syntax, or semantics of some natural language.

These are three related, but different kinds of representations.

A well developed Ontology would include:

– Objects (things) in the domains of interest– The relationships between those things– The properties (and property values) of those things– The functions and processes involving those things– Constraints on and rules about those things


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Gene Ontology

:Ontologies: Scientific Data Sharing Made Easy by Nicole Washington & Suzanna Lewis @2008


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Types of Ontologies

upper-level Ontologies – DOLCE : Domain Ontology for Linguistic and Cognitive Engineering– SUMO :Suggested Upper Merged Ontology– BFO : Basic Formal Ontology

mid-level, domain-spanning Ontologies – PSL : Patterns to Specify Processes – by NIST

Domain Ontologlies – Geospatial Ontologies. Medical Ontologies ..etc.


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Bio medical Ontologies

The OBO Foundry: A suite of biomedical ontologies to support reasoning and data integration SNOMED Unified Medical Language System National Cancer Institute Thesaurus HL7 Reference Information Model International Classification of Functioning, Disability and Health

List of Biomedical Ontologies that use BFO BioTop: A Biomedical Top-Domain Ontology Common Anatomy Reference Ontology (CARO) Foundational Model of Anatomy (FMA) Gene Ontology (GO) Infectious Disease Ontology ( IDO Ontology for Biomedical Investigations (OBI Ontology for Clinical Investigations (OCI) Phenotypic Quality Ontology (PaTO) Protein Ontology (PRO) RNA Ontology (RnaO) Senselab Ontology Sequence Ontology (SO) Subcellular Anatomy Ontology (SAO) Vaccine Ontology (VO)


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BFO concepts

Examples of Basic Formal Ontology (BFO) concepts:

- Universal vs instances

- Continuant vs Occurrent - Similar to Substance, ( objects, entities etc) and Process

- You are a substance

- Your life is a process

- You are 3-dimensional

- Your life is 4-dimensional- Etc

- Independent vs Dependant


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Example of relations in OBO - Bio medical Ontology

Foundational : is_a, part_of– adult human is_a human

Spatial : located_in contained_in, contained_adjacent_to

Temporal : transformation_of,derives_from

preceded_by- larva transformation_of pupa

Participation: has_participant


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Ontology Representation languages

Resource Description Language(RDF), Web Ontology Language - OWL, OWL2, Common Logic .. Semantic Web Rule Langaue (SWRL) Rule interchange format (RIF) Simple Knowledge Organization Syemt(SKOS) CycL DOGMA (Developing Ontology-Grounded Methods and Applications) F-Logic (Frame Logic) KIF (Knowledge Interchange Format) UML, OBO, etc ….

Tools:Protégé, OntoEdit, WebODE Portals: The National Center for Biomedical Ontology (NCBO) has developed BioPortal 2.5, a Web-based platform for browsing,

visualizing, mapping, and commenting on biomedical ontologies and terminologies http://bioportal.bioontology.org

Ontolog Forum has Open Ontology repository OOR sandbox – http://oor-01.cim3.net


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Animal Ontology

RDF graph

Ontology Summarization Based on RDF Sentence Graph byXiang Zhang seu,edu


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BioPortal.org


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BioPortal search results


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Standards Provide

Common structure and terminology Single data source for review (less redundant data) Standards allow use of common tools and techniques, common training single

validation of data Ontology = Good standard data Ontology = Semantic reasoning

ISO Standards that are Ontology related ISO 15926 in modeling business information

– Realtime Interoperability Network Grid– used for Content collaboration, reference data– publication and collaborative generation of reference data - Mathew West, Information junction

ISO 11179 standard - EPA ISO 15000- Supports data modeling


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Inventory of Relevant Standards for EHRSystems

• Architecture standards - HL7 versions 2.x/3, CORBA, MDA, HISA • Modelling standards - UML, CEN 15300: “CEN Report: Framework for formal modelling of healthcare security policies” • Communication standards - CEN 13608: “Security for healthcare communication”, CEN 13606: “Electronic healthcare record communication” • Infrastructure standards - ISO 17090: “Public key infrastructure”, ETSI TS 101733: “Electronic Signature Formats” • Privacy standards - ASTM E1987-98: “Standard guide for individual rights regarding health information”, CEN 13729: “Secure user identification - Strong authentication using microprocessor cards”; ISO/IEC PDTS Pseudonymisation Practices for the Protection of Personal Health Information and Health Related Services • Safety standards - CEN 13694: “CEN Report: Safety and security related software quality standards for healthcare”; ISO/DTS 25238 Classification of Safety Risks • Quality standards - ISO 9000: • Terminology and ontology standards - UMLS, SNOMED • Identifier and identification schemes - LOINC, ASTM E1714-00: “Standard guide for properties of a Universal Healthcare Identifier”

By European Commission – DG Information Society


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Example, Zachman framework


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Where does Ontology fit into EA?

In Zachman framework – the second row first column – One needs to develop a semantic model.. In olden days we called it

conceptual information model.. (CIM) Ontology can be developed as part of semantic model.. List of things

that exist and their properties and relationships and process associated with them ..etc..

At system level these models can be based to develop further data models and process models depending on the methodology used..

– UML diagrams – Object diagrams / Class diagrams / activity diagrams– ER diagrams

FEAF supports semantic modeling similar to Zachman.. DoDAF, on has to develop Ontologies as part of Information View..


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Ontology as Knowledge base


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Ontology as Knowledge base

Students talk with a patient, tutor, consultant, or lab technician.

All dialogs use the same ontology and knowledge base. Source: Adaptivity in a multi-agent clinical simulation

system, by S. Nirenburg,M. McShane, S. Beale, & B. Jarrell, http://www.cis.hut.fi/AKRR08/papers/nirenburg.pdf


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Usage of Ontologies in SOA

Ref: An Ontology-Driven Service-Oriented Approach by Saïd Izza, Lucien Vincent, Patrick Burlat


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Semantic Web Layers:


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What problems does Ontology help to solve..

Same word has different meaning and same meaning has different words… Ontology can help define and standardize the usage of terms and meanings and relationships for the organization or domain..

Enterprise wide, domain wide interoperability– Currently: system-of-systems, vertical stovepipes– Ontologies act as conceptual model representing enterprise consensus

semantics Heterogeneous Data Problem

– Different organizational units, Service Needers/Providers have radically different databases

– what’s the format? - Syntactic– how are they structured? - Structure– what do they mean ? – Semantic– They all speak different languages (access, description, schemas,

meaning)


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Leo Obrst’s Ontology Spectrum

Interoperability

weak semanticsweak semantics

strong semanticsstrong semanticsIs Disjoint Subclass of with transitivity property

Modal Logic

Logical Theory

Thesaurus Has Narrower Meaning Than

Taxonomy Is Sub-Classification of

Conceptual Model Is Subclass of

DB Schemas, XML Schema

UML

First Order Logic

RelationalModel, XML

ER

Extended ER

Description LogicDAML+OIL, OWL

RDF/SXTM

Syntactic Interoperability

Structural Interoperability

Semantic Interoperability


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Benefits of Ontology

For humans Ontology enables better access to information and promotes shared understanding of information, terms and concepts

– Data Information Knowledge Wisdom

For computers Ontologies enable comprehension of Information and more extensive processing

– Knowledge Information Data & processing

Systems that are developed, based on well developed ontologies would support Integration and syntactic and semantic interoperability

Supports latest architecture patterns for web services– SOA to provide semantic services– Semantic WebTherefore serve and harness the power of computing and new technologies to enhance human wisdom

decision and making.


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Benefits of Ontology

Interoperability: When interfacing two components, access the ontology of each component to design a mapping between different concepts in different components.

Browsing/searching: The meta-knowledge within an ontology can assist an intelligent search engine with processing your query. For example, if a query returns no results, then the ontology could be used to automatically generalize the query to find nearest partial matches.

Reuse: Why waste time and money rebuilding component X when X already exists in someone else’s library?

Structuring: It may be faster to build new systems via “ontological bootstrapping”; i.e. use the conceptualizations in ontologies to assist you with structuring the knowledge in a new domain.


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Conclusion

Modern medical information management is a knowledge intensive activity requiring a high degree of interoperability across various health management entities and systems to provide consistent optimal services across.

Usage of standard based ontology will help with interoperability, systems integration, and should be developed as part of conceptual information modeling (CIM) while developing Enterprise Architecture, for the organization.

An ontology based approach which includes security policies and standards provide a framework for better interactions in a distributed medical systems environment without the limitation of the traditional approach. In addition to interoperability, this would also support SOA and semantic web architectural patterns.


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References

Bio-ontologies: current trends and future directions,by Olivier Bodenreider and Robert Stevens

Introduction to Bio medical Ontologies by Barry Smith http://www.bioontology.org/seminar-series

Semantic Interoperability and Strategies for the Standardization of Medical Information: epSOS project : By Barry Smith

National center for Biomedical Ontology : http://www.bioontology.org/ Ontologies for Intelligence Community, by Dr.Leo Obrst, MITRE Ontology Forum : http://ontolog.cim3.net/cgibin/wiki.pl?WikiHomePage Integrating Semantic Systems, Expressing, sharing, and using knowledge, Dr John

Sowa http://www.jfsowa.com/talks/iss.pdf Standford’s Protégé, Ontology development tool : http://protege.stanford.edu/ Cost Benefits of Ontology – Tim Menzies, NIST Zachman framework – zifa.com FEAF framework- http://www.cio.gov/documents/fedarch1.pdf

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