biomedical informatics the lexical grid project: lexgrid christopher g. chute, md drph professor and...

Biomedical Informatics

The Lexical Grid Project: LexGrid

Christopher G. Chute, MD DrPHProfessor and Chair, Biomedical Informatics

Mayo Clinic College of MedicineRochester, Minnesota

Ontolog Forum14 December 2006


The Lexical Grid Project: LexGrid

Acknowledgements:Harold Solbrig

James BuntrockThomas Johnson

Dan Armbrust

© 2006 Mayo Clinic College of Medicine 3


Outline - LexGrid

• Overview• Functional Features• Problem Framing• LexGrid History• Present Status• Implementations• Future



Overview

• The LexGrid package represents a comprehensive set of software and services to load, publish, and access vocabulary or ontological resources.

• The package is based upon an open standard• HL7 CTS (CTS II intended as more complete)

• Reference implementations as open source• http://informatics.mayo.edu• Migration to OHF



LexGridInterlocking Components• Standards - access methods

(programming APIs) and formats need to be published and openly available.

• Tools - standards based tools must be readily available.

• Content - commonly used vocabularies and ontologies have to be available for access and download.



The Lexical Grid• Terminology as a commodity resource

• Accessible online• under a common model• through a set of common API's• in web-space on web-time

• cross-linked• loosely coupled• published individually, when ready

• exportable• locally extendable • globally revised• open source tooling to browse, edit, etc



Overview purposes

• Provides a single information model flexible enough to represent yesterday’s, today’s and tomorrow’s terminological or ontological resources

• Allows resources to be published online, cross-linked, and indexed on demand

• Provides standardized building blocks and tools that allow applications and users to take advantage of the content where and when it is needed

• Provide consistency and standardization required to support large-scale vocabulary adoption and use



LexGrid Features• Accommodation of multiple vocabulary and ontology

distribution formats.• Support of multiple data stores to accommodate

federated vocabulary distribution.• Consistent and standardized access across multiple

vocabularies.• Rich API for supporting lexical and graph search and

traversal.• Fully compatible with HL7-CTS implementation.• Support for programmatic access via Java, .NET, and

web services.• Open source tooling and code to facilitate adoption

and use.



LexGrid Users

• Vocabulary service providers. Describes organizations currently supporting externalized API-level interfaces to vocabulary content.

• Vocabulary integrators. Describes organizations that desire to integrate new vocabulary content or relations to be served locally.

• Vocabulary users. Describes persons and organizations desiring common, consistent access to vocabulary content for a supporting multiple application development uses.



LexGridNode

Data

Services

Java

.NET

...

Import

Editors

Browsers

Query Tools

XML

Browse andEdit

Export

Embed

LexBIG

Index

LexGrid Conceptual ArchitectureComponentsRRF

OBO

OBO

Text

ProtégéCTS

Text

OWL

XML

Lex*

WebClients

LexGrid

Service IndexRegistry



LexGrid Node

• The logical persistence layer for storing and managing vocabulary content.

• The LexGrid node utilizes relational database management systems for management of data and indexing functions.

• LexGrid nodes have been successful installed and tested using MySQL, Postgres, UDB/DB2, Oracle, Hypersonic, and LDAP/BDB.

LexGridNode

Data

Services

WebClients

Java

.NET

...

Import

Editors

Browsers

Query Tools

XML

Browse andEdit

Export

Embed

LexBIG

Index

RDF

Protégé

RDF

OWL

Protégé CTS

Text

OWL

XML

Lex*

LexGridService Index

Registry



The Import Toolkit(s)

• Provides an API and a set of administration tools to load, index, publish, and manage vocabulary content for the vocabulary server.

• Standard formats and models that have been developed include:

•Rich Release Format (RRF)•Ontology Web Language (OWL)•LexGrid XML•Text Delimited•Ontylog XML (Apelon) format•Open Biomedical Ontology (OBO)

LexGridNode

Data

Services

WebClients

Java

.NET

...

Import

Editors

Browsers

Query Tools

XML

Browse andEdit

Export

Embed

LexBIG

Index

RDF

Protégé

RDF

OWL

Protégé CTS

Text

OWL

XML

Lex*


Registry



The Export Toolkit(s)

• Provides an API and set of administration tools to export content in a standard format from a LexGrid node.

• Standard formats provided for export include:• LexGrid XML• OWL

LexGridNode

Data

Services

WebClients

Java

.NET

...

Import

Editors

Browsers

Query Tools

XML

Browse andEdit

Export

Embed

LexBIG

Index

RDF

Protégé

RDF

OWL

Protégé CTS

Text

OWL

XML

Lex*


Registry



The LexGrid Editor

• A light weight editor for creating, modifying, and changing vocabulary content.

• The LexGrid Editor is an Eclipse Based application that supports multi vocabulary query and browsing, interactive views, and logging and auditing.

• Recent enhancements have provided extensions to accommodate value set creation and management.

LexGridNode

Data

Services

WebClients

Java

.NET

...

Import

Editors

Browsers

Query Tools

XML

Browse andEdit

Export

Embed

LexBIG

Index

RDF

Protégé

RDF

OWL

Protégé CTS

Text

OWL

XML

Lex*


Registry



LexGrid Principles• LexGrid software is based on a model driven

architecture.• The LexGrid model is maintained in XML Schema

format• Represents a core component of design.

• The LexBIG API• Java-based API to LexGrid content is formally

modeled • Accommodates registration of additional load, index,

and search functions• Provides a conscious separation of service and data

classes in order to support deferred query resolution and software iterators



LexGrid Model

• Lexical Semantics• Names• (Textual) Definitions• Comments• Other non-classification property

• Context• Languages and dialects• Communities and specialties• Localizations

• Logical Semantics• Roles and Relations



LexGrid Model• Proposal for standard storage of controlled

vocabularies and ontologies• Flexible enough to accurately represent a wide

variety of vocabularies and other lexically-based resources

• Defines • How vocabularies should be formatted and

represented programmatically• Several different server storage mechanisms

• relational database, LDAP and an XML format.



LexGrid ModelCoding Scheme

RelationsConcepts

Properties

cd codingSchemes

describable

codingScheme

concepts::conceptsdescribable

relations::relations

describable

relations::association

relations::

associationInstance

associatableElement

relations::associationTarget

versionableAndDescribable

concepts::codedEntry

concepts::property

concepts::comment

concepts::definition

concepts::presentation

0..1+concepts 0..*+relations

1..*+association

0..*+sourceConcept

0..*+targetConcept

1..*+concept

0..*+property



Model: Code Systems• Each service defined to the LexGrid model can

encapsulate the definition of one or more vocabularies.

• Each vocabulary is modeled as an individual code system, known as a codingScheme.

• Each scheme tracks information used to uniquely identify the code system, along with relevant metadata.

• The collection of all code systems defined to a service is encapsulated by a single codingSchemes container.



Model: Concepts• A code system may define zero or more coded

concepts, encapsulated within a single container. • A concept represents a coded entity (identified in the

model as a codedEntry) within a particular domain of discourse.

• Each concept is unique within the code system that defines it.

• Must be qualified by at least one term or designation, represented in the model as a property.• Each property is an attribute, facet, or some other characteristic that may represent or help define the intended meaning of the encapsulating codedEntry.

• A concept may be the source for and/or the target of zero or more relationships.



Model: Relations• Each code system may define one or more containers to

encapsulate relationships between concepts.• Each named relationship (e.g. “hasSubtype” or “hasPart”) is

represented as an association within the LexGrid model.• Each relations container must define one or more association.• May also further define the nature of the relationship in terms of

transitivity, symmetry, reflexivity, forward and inverse names, etc.• Multiple instances of each association can be defined, each of

which provide a directed relationship between one source and one or more target concepts.

• Source and target concepts may be contained in the same code system as the association or another if explicitly identified.

• By default, all source and target concepts are resolved from the code system defining the association.

• The code system can be overridden by each specific association, relation source (associationInstance), or relation target (associationTarget).



Available Representationsof the LexGrid Model

• The master representation of the LexGrid model is provided in XML Schema Definition (XSD) format.

• Conversions to other formal representations are available, including XML Metadata Interchange (XMI) and Unified Modeling Language (UML).

• Implementation or technology-specific renderings of the model also exist.

• Relational database schema • (MySQL, PostgreSQL, DB2, Oracle, etc)

• Lightweight Directory Access Protocol (LDAP) schema• Programming interfaces generated from the formal

representation include Java bean interfaces based on the Eclipse Modeling Framework (EMF) and Castor frameworks.



Disease UnderstandingConstrained by Knowledge

• Carolus Linnaeus Carl von Linné

• Genera Morborum (1763)

• Underscored Content Difficulty• Pathophysiology vs Manifestation

e.g. Rabies as psychiatric disease



The Genomic Era• The genomic transformation of medicine far

exceeds the introduction of antibiotics and aseptic surgery

• The binding of genomic biology and clinical medicine will accelerate

• The implications for shared semantics across the basic science and clinical communities are unprecedented

• The implications for Public Health surveillance and inference are profound



From Practice-based Evidenceto Evidence-based Practice

PatientEncounters

ClinicalDatabases Registries et al.

ClinicalGuidelines

Medical Knowledge

ExpertSystems

DataData InferenceInference

KnowledgeKnowledgeManagementManagement

DecisionDecisionsupportsupport

OntologyShared Semantics

Vocabularies &Terminologies



The Historical Center of theHealth Data Universe

Clinical DataClinical Data

Billable DiagnosesBillable Diagnoses




Copernican Health Data Universe


Clinical DataClinical Data(Niklas Koppernigk)

GuidelinesGuidelines

Scientific LiteratureScientific Literature

Medical LiteratureMedical Literature

Clinical DataClinical Data

Genomic CharacteristicsGenomic Characteristics



Continuum from Nomenclature to Classification

• Patient Data is Highly Detailed• Modifiers: Anatomy, Stage, Severity, Extent• Qualifiers: Probability, Temporal Status

• Aggregate Uses Require Categorization• Granularity of Classifiers

• Focused Groups and Strata for CQI/Outcomes• Broad Statistical/Fiscal Groups



Familiar Points Along Continuum Modern Health Vocabularies

• Nomenclature – Highly Detailed Descriptions (SNOMED)

• Classification – Organized Aggregation of Descriptions into a Rubric (ICDs)

• Groupings – High Level Categories of Rubrics (DRGs)

Detailed GroupedNomenclatureNomenclature ClassificationClassification GroupsGroups



Blois, 1988Medicine and the nature of vertical reasoning • Molecular: receptors, enzymes, vitamins, drugs• Genes, SNPs, gene regulation• Physiologic pathways, regulatory changes• Cellular metabolism, interaction, meiosis,…• Tissue function, integrity• Organ function, pathology• Organism (Human), disease• Sociology, environment, nutrition, mental health…



The Continuum Of Biomedical InformaticsBioinformatics meets Medical Informatics

0

1

2

3

4

5

6

7

8

9

10

Biology Medicine

Chasm of Semantic Despair



Feudal CognitionIntellectual Semantic Baronies

• Genetic variation – Genomics • Haplotypes – Statistical Genomics• Molecular – Metabolomics, Proteomics• Binding – Molecular simulation• Pathways – Physiology and Systems Biology• Symptoms – Consumer Health• Rx and Px – Clinical Medicine• Risk – Public Health, Epidemiology• Social impact – Sociology, Health Economics



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Aggregation Logics by domainrule-based aggregations

Decision Support Decision Support and Error Detectionand Error Detection

Public Health andPublic Health andSurveillanceSurveillance

Reimbursement Reimbursement and Management and Management

Outcome Research Outcome Research and Epidemiologyand EpidemiologyFindingsFindings InterventionsInterventionsEventsEvents



Making Shared Context Explicit

CONCEPT

Referent

Refers ToSymbolises

Stands For“Rose”,“ClipArt”

Refers ToSymbolises

Stands For“Rose”,“ClipArt”

CONCEPT

Symbol Symbol

“I see a ClipArt image of a rose”

Context Context

Formal SharedContext

Terminologies Terminologies

[From Solbrig]



Proliferation of Content“Have it your way” Vocabulary Models

• Major ontologies• SNOMED CT; Gene Ontology; LOINC; NDF-RT• UMLS Metathesaurus; NCI Thesaurus• HL7 RIM and Vocabulary; DICOM RadLex • CDC bioterrorism PHIN standards• caBIG DSR / CDEs (Common Data Elements)

• All created with differing formats and models• Mechanisms for content sharing

• Research Area



History of Terminology Servicesin the US

• YATN: yet another terminology service 1996• Mayo, Kaiser, Lexical Technology

• MetaPhrase – Lexical Technology 1998• LQS: Lexicon Querry Services; 3M 1998• Mayo Autocoder: UI to YATN suite 2000• CTS: Common Terminology Services 2003

• HL7 balloted standard 2004• LexGrid: superset CTS, ref. implementation – 04

• http://informatics.mayo.edu



Mayo’s Work with Problem ListInterface Design

• Premise upon Terminology Server• MetaPhrase Prototypes on the Network

• Iterative Usability Lab Evaluations• Mock-ups in VB, Delphi, Java, …

• Evolve Toward Subset of Functional Needs• Problem List Specific• Drive Specification and Operation of T Server



Terminology Services for Humans



Common Terminology Services (CTS) • An HL7 ANSI standard

• Defines the minimum set of requirements for interoperability across disparate healthcare applications

• A specification for accessing terminology content• The CTS identifies the minimum set of functional

characteristics a terminology resource must possess for use in HL7.

• A functional model• Defining the functional characteristics of vocabulary as

a set of Application Programming Interfaces (APIs)



CTS APIs• Define the necessary functions for healthcare

terminology• Decouples terminology from the terminology service.• Technology independent

• Legacy database• Institutional infrastructure

• Provide common interface and reference model • I know what you mean by

• Code System• Coded Concept• Relationship



Mayo LexGrid ProjectOntology Services

• HL7 ANSI Standard• ISO Standard• Open specification• Provide consistency and standardization

required to support large-scale vocabulary adoption and use

• Common model, tools, formats, and interfaces• Standard terminology model (Excel to OWL)• Grid-nodal architecture•http://informatics.mayo.edu



Examples and Proof of Concept• NIH RoadMap: Nat. Center Biomedical Ontologies

• Mayo LexGrid project [MLG]• Clinical and basic science (Gene Ontology) communities

• NCI caBIG – Bioinformatics Grid [MLG]• HHS/ONC NHIN National Health Information Network

• IBM Data Coordination project• NLM/HL7 Coordination project; [MLG]

• CDC PHIN Public Health Information Network [MLG]• W3C Semantic Web

• XML/RDF/OWL • ISO 11179 metadata standards [MLG]



LexGrid Applications at Mayo forSemantic Annotation and Integration

• Basis for NLP (Natural Language Processing) entity annotation – clinical notes

• Harmonize data elements, values sets• Getting the data right

• Information retrieval and navigation• Getting the right data

• Grounding for data governance• Foundation for semantic interoperability



Cancer Biomedical Informatics Grid(caBIG)

• Coordinated infrastructure for Cancer Research• Clinical Trials, Integrative Cancer Research,

Tissue Banking and Pathology Tools• Vocabulary, Common Data Elements,

Architecture



caBIGGrid

caBIGGrid

caBIGNode

caBIGNode

OtherVocabulary

NCIThesaurus

LexGridCTS

Server

(Partial)Online Replica

Importer

OtherVocabulary

NCIThesaurus

NCI Meta-Thesaurus

LexGridCTS

Server

Local Replica

Importer

OtherVocabulary

NCI Meta-Thesaurus

LexGridCTS

Server

NCI

Import

KitNCI

Thesaurus

caBIGGrid

caBIGGrid

caBIGNodecaBIGNode

caBIGNodecaBIGNode

OtherVocabulary

NCIThesaurus

LexGridCTS

Server


Importer

OtherVocabulary

NCIThesaurus

LexGridCTS

Server


Importer

OtherVocabulary

NCIThesaurus

NCI Meta-Thesaurus

LexGridCTS

Server

Local Replica

Importer

OtherVocabulary

NCIThesaurus

NCI Meta-Thesaurus

LexGridCTS

Server

Local Replica

Importer

OtherVocabulary

NCI Meta-Thesaurus

LexGridCTS

Server

NCI

Import

KitNCI

Thesaurus

OtherVocabulary

NCI Meta-Thesaurus

LexGridCTS

Server

NCI

Import

KitNCI

Thesaurus

LexBIG Vision



LexPHINCDC Public Health Informatics Network

• Adoption of the LexGrid Model• Replace PHIN Vocabulary Services (VS)• Addresses genomic characterization of disease

• Span semantic chasm with Gene Ontology• Organized Value Sets

• Outbreak Management System• Biosurveillance and Biosense aggregation



LexPHIN Model

Concepts

Value Domains

Coding Scheme

Relations

Versions

versions::history

concepts::concepts

versionableAndDescribable

valueDomains::valueDomainversionableAndDescribable

codingSchemes::codingScheme

describable

relations::relations

valueDomains::valueDomains codingSchemes::codingSchemes

describable

service::service

+history

0..1

+concepts 0..1

+valueDomain 1..* +codingScheme 1..*

+relations 0..*

+valueDomains 0..1 +codingSchemes 0..1



Health Level Seven (HL7)

• Vocabulary and value domain management• Tooling for vocabulary submissions• Includes change events for HL7 governance

process



HL7 Value Domain Editor



NCBO – A Bridge Across the Chasm



NCBO Tools



Ontology List



Ontology Counts

Total Number of Ontologies 52NCBO Library 45Remote 7Number of Classes 175296**ontologies which have been parsed and indexed



Ontologies by Category



Expanded Categories



GO Biological Process Metadata



Concept Search



Search Results



MeSH Results



MeSH Hindlimb



BioPortalStanford UniversityArchana Vembakam and Lynn Murphy



LexGrid Future Issues• Federated vocabulary node synchronization and

registration/discovery.• API extensions to support local vocabulary extensions and

provider suggestions.• API extensions to support HL7/CTSII API (currently being

defined).• API extensions to support submission of vocabulary change

requests.• API extensions to load and map between additional vocabulary

formats.• ISO 11179 and LexGrid integration• Provide additional index services

• Synonymy and normalized search• Reasoner or classifier adaptation• Automated coding of medical records• Provide a light-weight Representational State Transfer (REST)

service implementation.



Conclusion• Biomedicine concepts have become complex

and intertwined• Big science model of future research

• 21st Century Medicine will require comparable and consistent data (Clinical and Genomic)

• Ontologies as formal models of concepts provide great opportunity

• Tools, content, and resources are becoming increasingly available

• LexGrid is emerging as an integrating force



Resources

LexGrid Projecthttp://informatics.mayo.edu/LexGrid

LexBIG Forge Sitehttp://gforge.nci.nih.gov/projects/lexbig

caBIG LexGrid CVShttp://cabigcvs.nci.nih.gov/viewcvs.cgi/lexgrid

NCBO Projecthttp://www.bioontology.org

biomedical informatics the lexical grid project: lexgrid christopher g. chute, md drph professor and...

Documents

access vocabulary

vocabulary users

vocabulary integrators

lexgrid package

ohf slide

new vocabulary content

lexgrid acknowledgements

lexgrid christopher