NeuroLOG: sharing neuroimaging data using an ontology-based - Irisa
NeuroLOG: sharing neuroimaging data using an ontology-based - Irisa
NeuroLOG: sharing neuroimaging data using an ontology-based - Irisa
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<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
AMIA 2011, Washington DC<br />
Software technologies for integration of process <strong>an</strong>d <strong>data</strong> in medical imaging<br />
<strong>NeuroLOG</strong>: <strong>sharing</strong> <strong>neuroimaging</strong> <strong>data</strong><br />
<strong>using</strong> <strong>an</strong> <strong>ontology</strong>-<strong>based</strong><br />
federated approach<br />
Bernard Gibaud 1 , Gilles Kassel 2 , Michel Dojat 3 , Bénédicte Batr<strong>an</strong>court 4 ,<br />
Fr<strong>an</strong>ck Michel 5 , Alb<strong>an</strong> Gaignard 5 , Joh<strong>an</strong> Montagnat 5<br />
1 INSERM / INRIA / CNRS / Univ. Rennes 1, IRISA Unit VISAGES U746, Rennes, Fr<strong>an</strong>ce<br />
2 Univ. de Picardie Jules Verne, MIS, EA 4290, Amiens, Fr<strong>an</strong>ce<br />
3 INSERM U836 / Univ. J. Fourier, Institut des Neurosciences, Grenoble, Fr<strong>an</strong>ce<br />
4 INSERM / CNRS / Univ. Pierre et Marie Curie, CRICM, UMR_S975, Paris, Fr<strong>an</strong>ce<br />
5 CNRS / UNS, I3S lab, MODALIS team, Sophia Antipolis, Fr<strong>an</strong>ce<br />
Supported<br />
by<br />
http://neurolog.polytech.unice.fr
Collaborative research in <strong>neuroimaging</strong><br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• What resources ?<br />
– Image <strong>data</strong> <strong>an</strong>d associated <strong>data</strong> (technical, clinical, etc.)<br />
– Image processing tools<br />
– Computing resources<br />
• Strategies: 2 possible<br />
approaches<br />
− Centralized (e.g. ADNI)<br />
− Federated (e.g. BIRN,<br />
caBIG, neuGRID,<br />
@NeurIST)<br />
Data<br />
Computing power<br />
Processing tools<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
3
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Overall system design<br />
AMIA 2011, Washington
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Major design choices<br />
• Federated system<br />
– federating independent legacy systems<br />
– flexibility for <strong>data</strong> org<strong>an</strong>ization<br />
• Mediation<br />
– use of <strong>an</strong> a priori-defined <strong>ontology</strong><br />
– consistent with a “Local as Views” approach (rather th<strong>an</strong> GaV)<br />
• Access control<br />
– security layer (X509 certificates + SSL ch<strong>an</strong>nels)<br />
– security policy<br />
a� Come up with a global federated view that hides <strong>data</strong><br />
distribution <strong>an</strong>d heterogeneity from the end-user<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
6
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Ontology design<br />
AMIA 2011, Washington
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Ontology: scope<br />
To assemble a common application <strong>ontology</strong> to provide a<br />
uniform <strong>an</strong>d consistent modelling of shared information,<br />
e.g. :<br />
− Images (Datasets)<br />
− Image acquisition <strong>an</strong>d image processing (Dataset processings)<br />
− Context of acquisition <strong>an</strong>d exploitation of the images (Studies,<br />
Subjects, Examinations, Centers, etc.)<br />
− Results of other kinds of explorations (Subject <strong>data</strong> acquisition<br />
instuments, Instrument variables, Assessments, Scores, etc)<br />
Use of this <strong>ontology</strong> to integrate heterogeneous <strong>data</strong><br />
Common relational schema<br />
AMIA 2011, Washington<br />
8
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Ontology: general approach<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• Application <strong>ontology</strong> (called Onto<strong>NeuroLOG</strong>)<br />
− <strong>based</strong> on a common modelling framework<br />
− 3-level structure<br />
• one Foundational <strong>ontology</strong>: i.e. DOLCE<br />
• Several Core ontologies<br />
• Several Domain ontologies<br />
• Major concerns<br />
− Re-use of existing ontologies (when applicable)<br />
− Documentation<br />
AMIA 2011, Washington<br />
9
Physical<br />
object<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
DOLCE: <strong>an</strong> <strong>ontology</strong> of particulars<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Particular<br />
Endur<strong>an</strong>t Perdur<strong>an</strong>t Quality Abstract<br />
Mental<br />
object<br />
Non-Physical<br />
object<br />
Social<br />
object<br />
Event Stative<br />
Achievement<br />
State<br />
Physical<br />
quality<br />
Accomplishment<br />
Process<br />
(Masolo et al., 2003)<br />
Temporal<br />
quality<br />
Region<br />
AMIA 2011, Washington<br />
Time<br />
interval<br />
10
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Ontology: 3-level structure<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Application <strong>ontology</strong> (called Onto<strong>NeuroLOG</strong>)<br />
one Foundational <strong>ontology</strong> (DOLCE)<br />
Several Core ontologies<br />
Several Domain ontologies<br />
AMIA 2011, Washington<br />
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Ontology: 3 representations<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
1. OntoSpec representation (Kassel, 2005)<br />
Semi-formal notation (rich sem<strong>an</strong>tics)<br />
Numerous axioms<br />
2. OWL-Lite<br />
Edited with PROTÉGÉ<br />
Tailored to perform inferences with CORESE (search<br />
engine)<br />
3. Federated relational schema<br />
Entities <strong>an</strong>d relations are closely linked to concepts <strong>an</strong>d<br />
relations of the <strong>ontology</strong><br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Example of OntoSpec representation<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
AMIA 2011, Washington
Ontology: 3 representations<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
1. OntoSpec representation (Kassel, 2005)<br />
Semi-formal notation (rich sem<strong>an</strong>tics)<br />
Numerous axioms<br />
2. OWL-Lite<br />
Edited with PROTÉGÉ<br />
Tailored to perform inferences with CORESE (search<br />
engine)<br />
3. Federated relational schema<br />
Entities <strong>an</strong>d relations are closely linked to concepts <strong>an</strong>d<br />
relations of the <strong>ontology</strong><br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
14
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Onto<strong>NeuroLOG</strong>: OWL-Lite representation<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
AMIA 2011, Washington
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Instruments’ descriptions<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
AMIA 2011, Washington
Ontology: 3 representations<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
1. OntoSpec representation (Kassel, 2005)<br />
Semi-formal notation (rich sem<strong>an</strong>tics)<br />
Numerous axioms<br />
2. OWL-Lite<br />
Edited with PROTÉGÉ<br />
Tailored to perform inferences with CORESE (search<br />
engine)<br />
3. Federated relational schema<br />
Entities <strong>an</strong>d relations are closely linked to concepts <strong>an</strong>d<br />
relations of the <strong>ontology</strong><br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
17
Ontology<br />
V2.2<br />
Dataset processing<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Study<br />
Examination<br />
Dataset<br />
Federated Relational Schema<br />
Variables<br />
Instrument<br />
Assessment<br />
Subject<br />
Scores<br />
Experimental<br />
Groups of Subjects<br />
MR protocol<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
18
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Data integration<br />
AMIA 2011, Washington
Software architecture<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
20
Integration mech<strong>an</strong>ism<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
21
<strong>NeuroLOG</strong> Server<br />
get/write<br />
files & <strong>data</strong>sets<br />
Local<br />
storage<br />
resource<br />
Interface with other Services<br />
Data m<strong>an</strong>ager<br />
Data & Meta<strong>data</strong> m<strong>an</strong>agement design<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
<strong>NeuroLOG</strong><br />
Client<br />
Web services<br />
Meta<strong>data</strong> m<strong>an</strong>ager<br />
write<br />
results<br />
<strong>NeuroLOG</strong> DB<br />
read (jdbc interface)<br />
Data Federator<br />
read<br />
Site-specific DB<br />
Site 1<br />
Web services<br />
<strong>NeuroLOG</strong> Server<br />
Data Federator<br />
Site 2<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Meta<strong>data</strong> mapping<br />
• Data Federator: relational <strong>data</strong> mapping <strong>an</strong>d<br />
federation tool (Business Object / SAP)<br />
IRISA I3S<br />
GIN<br />
Data Federator /<br />
global<br />
Data<br />
Federator /local<br />
<strong>NeuroLOG</strong><br />
Sh<strong>an</strong>oir<br />
Global federated view<br />
Data Federator /<br />
global<br />
Data<br />
Federator /local<br />
<strong>NeuroLOG</strong><br />
I3S<br />
Data Federator /<br />
global<br />
Data<br />
Federator /local<br />
<strong>NeuroLOG</strong><br />
GIN-DMS<br />
Global federated schema<br />
derived from project <strong>ontology</strong><br />
(Onto<strong>NeuroLOG</strong>).<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Sem<strong>an</strong>tic <strong>data</strong><br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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Query<br />
interface<br />
Architecture: sem<strong>an</strong>tic module<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Sem<strong>an</strong>tic queries<br />
engine (CORESE)<br />
Querying<br />
Querying<br />
Querying<br />
Mapping file (XML)<br />
Template file (XML)<br />
Sem<strong>an</strong>tic repository<br />
Ontology (OWL LITE)<br />
Images<br />
Meta-<strong>data</strong> (RDF)<br />
METAMorphoses<br />
(SQL ↔ RDF)<br />
Data Federator<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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Software architecture: client software<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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Client – Querying meta<strong>data</strong> <strong>an</strong>d<br />
accessing <strong>data</strong><br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• Search <strong>data</strong>sets related to selected subjects <strong>an</strong>d produced in selected studies<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Client - Viewer<br />
AMIA 2011, Washington
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Sem<strong>an</strong>tic query example (in SPARQL):<br />
EDSS scores with ambulation score
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Results: system<br />
deployment<br />
AMIA 2011, Washington
Rennes<br />
Paris<br />
CAC-DB<br />
IRISA<br />
(CHU Rennes)<br />
<strong>NeuroLOG</strong> platform<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
IFR49<br />
(La Pitié Salpétrière)<br />
Grenoble<br />
Gin-DMS<br />
Sophia Antipolis<br />
Neuro-DMS<br />
GIN<br />
(Michalon Hospital)<br />
I3S site<br />
(technical)<br />
INRIA<br />
(Centre A Lacassagne)<br />
• 5 sites federated<br />
– 4 legacy <strong>data</strong>bases<br />
– 12 studies<br />
– > 70 subjects<br />
– MS<br />
– Brain tumors<br />
– AD<br />
– > 500 <strong>data</strong>sets<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
Discussion<br />
AMIA 2011, Washington
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Discussion: <strong>ontology</strong><br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• Domains that could not be included<br />
− Ontology of Regions of Interest (image ROIs)<br />
− Ontology of <strong>an</strong>atomical structures<br />
• Need of convergence with other ontologies, e.g. NIF<br />
− Need to map BFO-<strong>based</strong> ontologies with our DOLCE<strong>based</strong><br />
ontologies<br />
AMIA 2011, Washington<br />
33
<strong>NeuroLOG</strong> ANR-06-TLOG-024<br />
Discussion: mediator<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• Data federator (SAP): the pros<br />
− St<strong>an</strong>dard interface (jdbc)<br />
− Fully dynamic queries<br />
− Perform<strong>an</strong>ce<br />
− User interface to defined mappings<br />
• Data federator (SAP): the cons<br />
− No automatic re-configuring in case of error<br />
− NOT opensource<br />
• Alternative solutions<br />
− OGSA-DAI / OGSA-DQP (e.g. used in BIRN, @NeurIST)<br />
− Fully sem<strong>an</strong>tic integration framework<br />
AMIA 2011, Washington<br />
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Conclusion / Perspectives<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• We have presented a system for <strong>sharing</strong> image <strong>data</strong> <strong>an</strong>d<br />
associated meta<strong>data</strong> according <strong>an</strong> <strong>ontology</strong>-<strong>based</strong><br />
federated approach<br />
- Most of our objectives (not all !) could be met<br />
- We are currently applying for a continuation of this work in focused<br />
<strong>neuroimaging</strong> research applications<br />
• We remain convinced that our <strong>ontology</strong>-<strong>based</strong> approach<br />
is a promising one<br />
– Intelligent <strong>data</strong> querying <strong>an</strong>d mediation<br />
– Complementary to regular relational querying<br />
• However, it raises the issue of the convergence with<br />
other ontologies developed elsewhere, e.g.<br />
– NIF* / BIRN** in the USA<br />
– @NeurIST in Europe<br />
* Neuroscience Information Framework<br />
** Biomedical Informatics Research Network<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
35
Acknowledgements<br />
Software technologies for integration of process, <strong>data</strong> <strong>an</strong>d knowledge in medical imaging<br />
• ANR, for its fin<strong>an</strong>cial support<br />
• All the people having contributed to <strong>NeuroLOG</strong>, espec.<br />
− Farooq Ahmad<br />
− Christi<strong>an</strong> Barillot<br />
− Pascal Girard<br />
− David Godard<br />
− Di<strong>an</strong>e Lingr<strong>an</strong>d<br />
− Grégoire Mal<strong>an</strong>dain<br />
− Mél<strong>an</strong>ie Pélégrini-Issac<br />
− Xavier Pennec<br />
− Javier Rojas Balderrama<br />
− Bacem Wali<br />
• And all our clinical partners, especially<br />
− Gilles Ed<strong>an</strong>, Je<strong>an</strong>-Christophe Ferré <strong>an</strong>d Je<strong>an</strong> Fr<strong>an</strong>çois Lebas<br />
<strong>NeuroLOG</strong> ANR-06-TLOG-024 AMIA 2011, Washington<br />
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