An modular approach to fMRI metadata in a Virtual Laboratory

-generic tools for specific problems

M. Scott Marshall, Kasper van den Berg, Kamel Boulebiar, Piter de Boer, Marco Roos, Tristan

Glatard, Silvia OlabarriagaVirtual Laboratory for e-science (VL-e)

University of Amsterdam

Outline

• Vision – an e-science virtual laboratory

• Everything is a Resource - Explicit Metadata Support

• Components – AIDA web services

• Platforms – Taverna, Web, Vbrowser

• What we did to manage fMRI data

Vision: Concept-based interfaces

• The scientist should be able to work in terms of commonly used concepts.

• The scientist should be able to work in terms of personal concepts and hypotheses.

- Not be forced to map concepts to the terms that have been chosen for a given application.

What is metadata (in this talk)?

• Metadata: data about data• Metadata can be syntactic such as a data

type, e.g. Integer.• Metadata can be semantic such as

chromosome number.• Note: not always ontology, but metadata can

be stored in the Web Ontology Language (OWL)

Common approaches to metadata

• Code it into the GUI or application (in datastructures, object types, etc.)

• Create special tables or fields for it in a relational database

• Map it into substrings of filenames• Mix it in with data in proprietary file formats• Let the user figure it out• Conclusion: There is a need for semantic

disclosure.

The Semantic Gap

User ResourcesMiddlewareApplication

The Model in the middle

User ResourcesMiddlewareApplication

My Model

Model Model

RDF : a web format for knowledge

RDF is a W3C language to express statements.

RDF Triple: Subject Predicate ObjectGraph of Knowledge: Node Edge Node

9

Adaptive Information Disclosure (AID)participating in the VL-e project

The AIDA toolbox for knowledge extraction and knowledge management

in a Virtual Laboratory for e-Science

Example scenario of Taverna application

myModelmyExtendedModel

18/04/23 BioAID 12

Components of the AIDA toolbox used for Life Science knowledge extraction

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BioAID Disease Discovery workflow

AIDAAIDA

AIDAAIDA

OMIM service (Japan)OMIM service (Japan)

AIDA

AIDA

‘Taverna shim’

‘Taverna shim’

Taverna ‘shim’

Taverna ‘shim’

18/04/23 BioAID 15

BioAID Disease Discovery results

18/04/23 BioAID 16

Enriched ontology (snapshot)

Example scenario on Web platform

Looking at custom terminologies, ontologies for search in personalized index http://aida.science.uva.nl:9999/search/

VBrowser + AIDA

• VBrowser provides locators, viewers, access to grid storage and transport, a resource-oriented interface

• AIDA provides services for search, annotation, storage, and metadata extraction

VBrowser: Resource Overview

Location Bar

Grid Resources

Grid FTP

Reliable File Transfer

SRB (SARA)

Local Resources

MRI: more than structural information

perfusion MRI

functional MRI

anatomical

Functional MRI (fMRI): What do we do?

• Goal: observe brain function during cognitive or physical activity.

• Combination of stimulation and imaging.

• Based on the increase in blood flow to the local vasculature that accompanies neural activity in the brain.

fMRI

fMRI Paradigms in clinical fMRI

• Motor area• Language regions (Broca, Wernicke)• Visual cortex

fMRI in Clinical:Preparation of Neurosurgery

Neurosurgery Planning

SOAPRouter

WorkersWorkflowManager

WorkerManager

Cacher

Logger NotifierDicom

Receiver

Exporter

Central Storage Facility

PACS

Checker

Neuro Navigator

Stimulus System

3 Tesla MRI

`

Viewing Workstation

Functional MRI: Analysis

MR scanner

Brain activation maps

StimulusSystem

fMRI scan Group Activation Map

fMRI use case

• Feature Extraction parameter sweeps are performed on the fMRI data on the grid.

• The desire is to study the results due to different combinations of parameters.

• Each parameter set serves as metadata associated with a particular result set location.

Metadata for fMRI data search

A quick peek at the VBrowser

A look at fMRI parameters (browsing RDF), RDF queries, SRB access:

http://staff.science.uva.nl/~ptdeboer/vlet/

Acknowledgements

• AIDA team: Marco Roos, Sophia Katrenko, Edgar Meij, Willem van Hage, Kasper van den Berg

• Vbrowser: Piter de Boer• VL-e Medical Imaging: Silvia Olabarriaga, Kamel Boulebiar,Tristan

Glatard• Guus Schreiber, Maarten de Rijke, Pieter Adriaans• Food Informatics partners: Wageningen University, TNO, Unilever, • Martijn Schuemie, Erasmus University Rotterdam• myGrid team, especially Katy Wolstencroft, Stian Soiland, Stuart

Owen, Andrew Gibson, Alan Rector, Robert Stevens, Carole Goble• Science Commons – Alan Ruttenberg• W3C Semantic Web Health Care and Life Sciences Interest Group

• http://adaptivedisclosure.org

• Work supported by VL-e and BioRange projects (BSIK grants)