1 O pen G ALEN Integrating Bio and Health Informatics: Integrating Bio and Health Informatics: Ontologies for Bridging Scales, Contexts Ontologies for Bridging Scales, Contexts and Customs and Customs Alan Rector Alan Rector Bio and Health Informatics Forum/ Bio and Health Informatics Forum/ Medical Informatics Group Medical Informatics Group Department of Computer Science Department of Computer Science University of Manchester University of Manchester [email protected][email protected]www.cs.man.ac.uk/mig img.man.ac.uk www.cs.man.ac.uk/mig img.man.ac.uk www.clinical-escience.org www.clinical-escience.org mygrid.man.ac.uk mygrid.man.ac.uk
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Integrating Bio and Health Informatics: Integrating Bio and Health Informatics: Ontologies for Bridging Scales, Contexts Ontologies for Bridging Scales, Contexts
and Customsand Customs
Alan RectorAlan Rector
Bio and Health Informatics Forum/Bio and Health Informatics Forum/Medical Informatics GroupMedical Informatics Group
Department of Computer ScienceDepartment of Computer ScienceUniversity of ManchesterUniversity of Manchester
An opportunity for An opportunity for E-Science / E-HealthE-Science / E-Health
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What is e-ScienceWhat is e-Science
• ‘e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.’
• ‘e-Science will change the dynamic of the way science is undertaken.’
John Taylor Director General of Research Councils
Office of Science and Technology
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The Semantic Web / GridThe Semantic Web / Grid
• “The Semantic Web is a vision: the idea of having data on the web defined and linked in a way, that it can be used by machines - not just for display purposes, but for using it in various applications.”
www.semanticweb.org
• “Our vision of the infrastructure that is needed to support the full richness of the e-Science vision draws on research and development in both the Grid and the Semantic Web, and adopts a service-oriented approach. We call it the Semantic Grid.”
• Confidentiality, Privacy and Consent– Keeping public confidence while enabling
research
• Information capture– Speed and ease of use require language
technology
• Information integration– Need common ontologies to bridge bio and
health information
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Social Policy ImperativeSocial Policy ImperativeConfidentiality, Privacy, Confidentiality, Privacy,
and Consentand Consent• Keeping public confidence while enabling research
– Balance individual risks and societal benefits
• Social policy research– Evidence-based debate rather than dogmatic disputation
• Technical means for enforcement– Grid & web infrastructure not yet adequate
Potential Show
Stopper
Good practice rigorously observed Good practice rigorously observed & sensibly enforced& sensibly enforced
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The Information Capture BottleneckThe Information Capture BottleneckWhat clinicians have heard, seen, thought, What clinicians have heard, seen, thought,
& done& done
• Speed & ease of use for entering clinicians– Care can’t wait– Training opportunities minimal
• Language technology– Doctors dictate; nurses write; annotators
annotate
• Quality– Much current information is unreliable
• possibly even dangerous
Information from people rather than machines…
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Information Integration Information Integration BottleneckBottleneck
“Joining up meaning”“Joining up meaning”• Differences in concepts
– “What is a gene?”– “What is a diseases?”
• Differences in purpose & relevance– Clinical care vs clinical research
• Differences in context– Mouse vs human anatomy
• Differences in granularity– Genetic, genomic, … organ…organism
• V31.22 Occupant of three-wheeled motor vehicle injured in collision with pedal cycle, person on outside of vehicle, nontraffic accident, while working for income
– and meanwhile elsewhere in ICD-10• W65.40 Drowning and submersion while in bath-tub, street
and highway, while engaged in sports activity
• X35.44 Victim of volcanic eruption, street and highway, while resting, sleeping, eating or engaging in other vital activities
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The Cost: Normalising (untangling) The Cost: Normalising (untangling) OntologiesOntologies
StructureFunction
Part-wholeStructure Function
Part-w
hole
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The Cost: Normalising (untangling) The Cost: Normalising (untangling) OntologiesOntologies
Making each meaning explicit and separateMaking each meaning explicit and separatePhysSubstance Protein ProteinHormone Insulin Enzyme Steroid SteroidHormone Hormone ProteinHormone^ Insulin^ SteroidHormone^ Catalyst Enzyme^