e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Ontologies in the context
of the Neurobase project
Bernard Gibaud
VisAGeS, U746 Inserm/INRIA, IRISA, Rennes
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Acknowledgements
• NeuroBase participants
• Ontology part
– Lynda Temal (ViSAGeS, Rennes)
– Gilles Kassel (LaRIA, Amiens)
– Michel Dojat (Inserm, Grenoble)
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Context: ressources produced by
research in neuroimaging
• Data, denoting knowledge about brain
– Functional maps
– Morphological and physiological abnormalities related to the
various brain diseases
– Behavioral data
• Know-how
– Exploration methods: paradigms, imaging techniques e.g.
specific MR sequences…
– Image processing tools
• Segmentation, registration, quantification, etc.
• Statistical analysis
– Image processing pipelines
• Suitable for a specific problem
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Specific motivations
• Integration of heterogeneous data At stake: feasibility of
– Image data
– Processed data
• Interpretation of image content
– Associated clinical information
• Interoperability of processing tools
large scientific studies,
and clinical trials
with thousands of
cases
At stake: feasibility of
open platforms (e.g. XIP)
– Input data : images and parameters
receiving portable
– Output data : images, registration data,
« plug-ins », and
etc.
deployment of wide– Semantics of data processing
scale GRID
implementation of image
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processing
e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Approach
Application
Application
Application
Mediator-based integration
Common semantic reference
wrapper
wrapper
wrapper
Data
Data
Data
Site #1
Proc. Tools
Site #2
Proc. Tools
Site #n
Proc. Tools
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Common ontology
• « a formal, explicit specification of a
shared conceptualization » (Gruber 1993)
– Necessary to write applications and
wrappers (entities, range of values)
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Ontology: scope
General concepts
(upper level ontology)
(non specific)
General concepts
of domain of interest
(domain-specific)
All other concepts
of domain of interest
(i.e. to deploy in a real life application)
Ex: process, state,
natural object, artefact,
etc.
Ex: patient, scan,
study, pathology,
image series, etc.
Ex: interictal state
(in epilepsy),
deep brain stimulation
(in Parkinson),
design matrices
(fMRI), etc.
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Neurobase ontology
• Scope
– Studies (subjects, experimental context, clinical aspects, etc.)
– Datasets and description of their content (images, ROI,
registration data, etc.)
– Image processing (processing tools, processing, etc.)
• Method
– Integration of multiple sources (fMRIDC, DICOM, Neurobase
partners’ experience)
– Representation : UML, then Protégé
• Implementation in the demonstrator: relational schema
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Results
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Taxonomy
Event
Scan
-Session
Assessment
Thing
Process
Study
Body
-Process
Data
-Processing
Object
Person
Anatomical
-Structure
Artefact
Acquisition
-Equipment
Processing
-Tool
Group
of people
Information
Specification
Report
Data
Experimental
-Group
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Datasets
Thing
Event
Scan
-Session
Process
Assessment
Study
Body
-Process
Artefact
Object
Data
-Processing
Person
Anatomical
-Structure
Acquisition
-Equipment
Group
of people
Information
Processing
-Tool
Specification
Report
Data
Experimental
-Group
Dataset
Reconstructed
Dataset
NonReconstructed
Dataset
MEEG
Data
MRRaw
Data
SPECT
Projection
Static
CT
Image
CT
Image
Dynamic
CT
Image
MR
Image
MR
Anat.
Image
Template
Dataset
SPECT
Image
PET
Image
MR
Funct.
Image
Static
PET
Image
MEG
Current
DipoleList
Registration
Dataset
Graph
Segmentation
Dataset
Mesh
Multi
Dimensional
Image
Dynamic
PET
Image
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Dataset : properties
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Reports
Thing
Event
Scan
-Session
Process
Assessment
Study
Body
-Process
Artefact
Object
Data
-Processing
Person
Anatomical
-Structure
Acquisition
-Equipment
Group
of people
Information
Processing
-Tool
Specification
Report
Data
Experimental
-Group
Report
InterpretationOf
DatasetComponent
InterpretationOf
MeshComponent
InterpretationOf
BinaryVoxel
Information
Scientific
Publication
DataProcessing
LogFile
Ethics
Commission
Authorization
InterpretationOf
VoxelValues
InterpretationOf
ProbabilisticVoxel
Information
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
InterpretationOfBinaryVoxelInformation : properties
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Data
Processing
Event
Scan
-Session
Thing
Process
Assessment
Study
Body
-Process
Artefact
Object
Data
-Processing
Person
Anatomical
-Structure
Acquisition
-Equipment
Information
Group
of people
Information
Processing
-Tool
Specification
Report
Data
Experimental
-Group
Process
Artefact
isInvolvedIn
Report
Data
Specification
Information
InData
Processing
hasValue
Atomic
0,1
0,*
Processing
Tool
hasPort
0,*
concernsPort
1
isValuedBy
1
0,*
Port
1
0,*
Data
Processing
1
involves
0,*
Dataset
Data
Processing
LogFile
0,1
0,1
inTheContext0f
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Discussion - ontology
• Need to evolve toward a formal ontology
– i.e. expressed in a logical language (e.g. OWL)
– Necessary for :
• Management of « intelligent » queries
• Wrappers
• Articulated to consensual (!) « foundational ontologies »,
– e.g. DOLCE (WonderWeb) or BFO (Barry Smith et al.)
– interoperability with external terminology systems, e.g.:
• Unified Medical Language System (UMLS, NLM)
• Foundational Model of Anatomy (FMA, UW Seattle)
• Difficult trade-off
– Complexity / practical usability
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Ontology: work in progess
Towards a formal ontology
for medical images and processing tools
in neuroimaging
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Methods
• Basic principles
– Modularity
– Re-use of existing components
• Foundational ontology
• (Core) Domain ontologies
– Use formal ontologies
• Methodology
– ONTOSPEC (Gilles Kassel et al.)
• Semi-formal approach
• Easy translation in OWL
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« A roadmap for data integration », nov. 27-28, 2006
Excerpt from an ONTOSPEC document
Guarino’s meta-properties
Essential Property /
Subsumption Link with Differentia
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Overview
DOLCE Particulars
Foundational
ontology
Reused
ontologies
I&DA
Participant roles
Documents
Core
ontologies
Reasonings OntoKADS
Programs & Software
Domain
ontologies
Medical images
COPS
New-built
ontologies
Image processing tools
Temal et al., FOMI 2006, Trento (Italy)
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Based on DOLCE
(Descriptive Ontology for Linguistic and
Cognitive Engineering)
IST WonderWeb project
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Dolce
e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Information & Discourse Acts (I& DA)
Conceptualizations: means by which Agents reason about the world
Proposition: to describe situations
Concept: to classify entities
Expressions: non-physical forms of knowledge ordered by a communication language
Inscriptions: forms of knowledge inscribed on some physical medium
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Datasets as Propositions
Datasets:
- expressed according to a Dataset Expression (i.e. encoding format)
- inscribed on some physical medium (i.e. File), or rendered as an Image
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Participant roles
Based on Guarino’s meta-properties (rigidity, identity, dependence, etc.) and
related classifications:
Role: Anti-Rigid (~R) and Dependent (+D)
Material role: Anti-Rigid (~R), Dependent (+D), with Identity criteria (+I)
Formal role: Anti-Rigid (~R), Dependent (+D), without Identity criteria (-I)
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Bruaux et al., K-CAP 2005, Banff (Canada)
e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Reasonings
Image generation processes (i.e. processing) are considered as Reasonings
because they operate in the non-physical world
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Ontology of Programs and Software (COPS)
Programs are involved in Reasonings (Actions) through relation AllowsToCarryOut
(representation of the programs’ functionality)
Conceptualizations or Expressions participate in such Reasonings as Data (i.e. input)
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or Result (i.e. output)
e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Current work
• To model Datasets content as functions
– (i.e. mathematical functions)
– Range, Domain
• Sampling characteristics
• To model Interpretations as Propositions relating, e.g.
segmented regions to real-life objects
– Anatomical structure associated to a 3D binary mask
– Pathological process (e.g. tumor evolution) associated to a time
series of 3D surfaces
• To model Processing Tools
– model input and output variables as Data and Results (formal roles)
– Model actual processing as Actions, in which Datasets may
participate (material roles)
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e-Science Workshop
« A roadmap for data integration », nov. 27-28, 2006
Conclusion / perspectives
• Experience from exploratory phase
– very positive
– intuition that potential impact is important in
neuroimaging, but also in other fields e.g.
genomics, or cancer research (CaBIC)
• Work being pursed
– Ontology (datasets, processing tools)
– Applications
• To get feedback from real-life applications
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