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A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases. Document Navigation: Ontologies or Knowledge Organisation Systems. Simon Jupp Bio-Health Informatics Group University of Manchester, UK Bio-ontologies SIG, ISMB 2007 Vienna, Austria.

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document navigation ontologies or knowledge organisation systems

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Document Navigation: Ontologies or Knowledge Organisation Systems

Simon Jupp

Bio-Health Informatics Group

University of Manchester, UK

Bio-ontologies SIG, ISMB 2007 Vienna, Austria

introduction

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Introduction

Document navigation over a Semantic Web

Ontologies are being developed as background knowledge to drive the Semantic Web.

Message: Formal ontologies are not the only knowledge artefact needed, artefacts with weaker semantics have their role and are the best solution in some circumstances

cohse conceptual open hypermedia service

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

COHSE (Conceptual Open Hypermedia SErvice)

Navigation via Hypertext is a mainstay of WWW

Problem:Links are typically embedded to Web pages; hard-coding, format restrictions, ownership, legacy resources, maintenance, Unary targets etc.

cohse architecture

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

COHSE Architecture

HTML Document in

Ontology

Knowledge Service

SKOS

DLS Agent

Search Engine

Resource Service

Linked HTML Document out

Annotation DB

sealife project

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Sealife project

  • A realisation of a Semantic Grid Browser, which links the currentWebto the emerging eScienceinfrastructure
  • Built on existing tools developed by partners:
  • COHSE, but also GoPubMed and others.
  • Applications: from cells via tissue to patients
    • Evidence-based medicine
    • Patent and literature mining
    • Molecular biology

www.biotec.tu-dresden.de/sealife

what is a sealife browser

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

What is a Sealife browser?

A Sealife browser is a browser that identifies concepts in texts and offers appropriate services based on these concepts.

Three main components:

  • an underlying “ontology” or set of “ontologies”
  • a text mining component
  • a service composition module
sealife use case study of disease

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Sealife use case - study of disease

NeLI: National electronic Library of Infection portal. Range of users but few links.

Given a document about Tuberculosis, where would users want to navigate to next?

http://www.neli.org.uk

background knowledge

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Background Knowledge

What style of knowledge model is best suited for navigation?

Do we need strict semantics, are they a help or hindrance?

All I want to say is this concept “has something to do with” this concept - this doesn’t fit well with formal ontology

e.g Polio has something to do with polio virus / polio disease / polio treatment - get me documents about all of them!

sealife background knowledge

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Sealife background knowledge

To cover molecular biology through to medicine we need a large knowledge artefact to serve as background knowledge for SeaLife. This artefact must support sensible navigation between documents on the web.

Luckily…

slide13

-Mosquito gross anatomy

-Mouse adult gross anatomy

-Mouse gross anatomy and development

-C. elegans gross anatomy

-Arabidopsis gross anatomy

-Cereal plant gross anatomy

-Drosophila gross anatomy

-Dictyostelium discoideum anatomy

-Fungal gross anatomy FAO

-Plant structure

-Maize gross anatomy

-Medaka fish anatomy and development

-Zebrafish anatomy and development

  • Protein covalent bond
  • Protein domain
  • UniProt taxonomy

-Pathway ontology

-Event (INOH pathway ontology)

-Systems Biology

-Protein-protein interaction

  • Sequence types and features
  • Genetic Context

BRENDA tissue / enzyme source

Phenotype

Proteins

Sequence

Pathways

Anatomy

Phenotype

Development

Plasmodium life cycle

Transcript

Gene products

Cell type

-NCI Thesaurus

-Mouse pathology

-Human disease

-Cereal plant trait

-PATO PATO attribute and value.obo

-Mammalian phenotype

-Habronattus courtship

-Loggerhead nesting

-Animal natural history and life history

-Arabidopsis development

-Cereal plant development

-Plant growth and developmental stage

-C. elegans development

-Drosophila development FBdv fly development.obo OBO yes yes

-Human developmental anatomy, abstract version

-Human developmental anatomy, timed version

- Molecule role

- Molecular Function

- Biological process

- Cellular component

eVOC (Expressed Sequence Annotation for Humans)

history of medical vocabularies

FMA

GALEN

DM&D

UMLS

OPCS3

OPCS4

OPCS4.3

CTV3

READ

SNOMEDInternational

ICPC

SNOMED-CT

SNOMED-2

SNOMED-RT

1975

1985

1995

2005

SNOPCPT

OPCSEmTree

SynopsisNosologiaeMethodicae

History of Medical Vocabularies

MeSH

ICD

ICD9

1603

1700

1785

1855

1900

1975

OPCSSNOPCPTMESHICD

what do we need for navigation

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

What do we need for navigation?

The bio-medical domain is rich in vocabularies and ontologies.

Large lexical resource including textual definitions and synonyms

There is a varying degree of semantics, expressivity and formality in these vocabularies (e.g. MeSH) and ontologies (e.g FMA). Most include some form of hierarchy. Hierarchies are well suited for driving navigation.

Question: Do we want strict sub/super class relationships? Or, do we want looser notations such as broader/narrower?

ontology or vocabulary

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Ontology or Vocabulary?

Initial approach to COHSE and SeaLife was to represent everything in OWL

The strict semantics of OWL do not always lend themselves to sensible navigation, conversion from vocabularies to OWL are difficult. It’s hard to model some things in OWL…

MeSH

OBO/OWL

Nucleuspart_ofCell

Head <-- Ear

<-- Nose

Cellhas_partNucleus - Not always True

Accident <-- Traffic Accident

<-- Accident Prevention

PolioDisease causedby PolioVirus

skos simple knowledge organisation system

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

SKOS (Simple Knowledge Organisation System)

Purpose: Subject Metadata and information retrieval

e.g. This document is about tuberculosis

Model for representing concept schemes, thesauri, classification system, taxonomies etc…

SKOS Concept is an individual of the class skos:concept, relationships are just asserted facts between (not restrictions!)

Model ideally suited for our task

e.g. prefLabe, altLabel, broader, narrower, related.

RDF/XML representation

http://www.w3.org/2004/02/skos/

conversion to skos

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Conversion to SKOS

  • relationship:part_of --> skos:broader ( e.g. finger part_of hand)
  • relationship:contains --> skos:narrower ( e.g. skull contains brain)
  • relationship:causes --> skos:related ( e.g. PolioDisease causes PolioVirus)

Sub properties:

inverse

skos:narrower

skos:broader

obo:part_of

obo:has_part

Leaves us open to migration back to OWL

conversion to skos1

SKOS

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Conversion to SKOS

OBO ontologies

MeSH

OWL ontologies

SNOMED

Concept Schemas

Taxonomies

NeLI

Thesauri

Other..

advantage of this approach

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Advantage of this approach

For a given concept e.g. “Polio Virus”, we can query multiple resources and bring related concepts together.

  • Rapid (and cheap!) generation of knowledge artefact
  • Take advantage efforts in multiple biomedical communities
  • We don’t have to make any strong ontological distinctions
disadvantage of this approach

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Disadvantage of this approach

Trade off: Lose the inferential power when querying a knowledge resource

Unwanted concepts & relationship - especially from OWL conversion e.g. ‘Physical Entity’, ‘Continuant’ etc….

Linking overload!

Inability to do inconsistency checking

Potentially large redundancy in our knowledge base

Maintenance and scalability (>1000000 concepts) - especially for dynamic hyper-linking.

plug for manchester s skos plug in prot g 4

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Plug for Manchester’s SKOS plug-in - Protégé 4

  • Instance hierarchy viewer
  • OBO or OWL --> SKOS wizards
  • Various rendering options
conclusion

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Conclusion

We need a large knowledge artefact that support navigation between related web resources

Rapid generation and reuse of existing terminologies (cheap)

Loosening the semantics of our model enables this with acceptable trade off

SKOS is a suitable model to represent our knowledge artefact

We have strong use cases from the life sciences - demos available

Still some open issues ….

acknowledgments

A Semantic Grid Browser for the Life Sciences Applied to the Study of Infectious Diseases

Acknowledgments

Manchester

Robert Stevens

Sean Bechhofer

Yeliz Yesilada

Other

COHSE developers

Sealife project

NeLI

Patty Kostkova

Thank you.