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Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

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NeuroLOG: sharing neuroimaging data using an ontology-based federated approach.

Bernard Gibaud¹, Gilles Kassel, Michel Dojat

¹INSERM / INRIA / CNRS / Univ. Rennes 1, IRISA Unit VISAGES U746, Rennes, France.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|December 24, 2011

Summary

NeuroLOG middleware enables sharing diverse neuroimaging data via a federated approach. This system uses ontologies and semantic search for better neurosciences data management and multi-centric studies.

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Area of Science:

Neuroscience
Computer Science
Data Management

Background:

Neuroimaging data is often heterogeneous and distributed across various repositories.
Managing and sharing these diverse datasets presents significant challenges for collaborative research.

Purpose of the Study:

To design and describe the NeuroLOG middleware data management layer.
To enable the sharing of heterogeneous and distributed neuroimaging data through a federated approach.

Main Methods:

Implementation of a multi-layer application ontology to capture information semantics.
Development of a derived Federated Schema to align disparate database schemata.
Integration of a semantic search engine for querying relational data translated into a semantic representation.

Main Results:

The NeuroLOG middleware facilitates the federation of large neuroimaging datasets.
The system enables the exploitation of knowledge embedded within the ontology.
Demonstrated the relevance and feasibility of a distributed approach for neurosciences data management.

Conclusions:

A federated approach is more realistic and offers strong perspectives for multi-centric neurosciences studies compared to centralized methods.
The NeuroLOG middleware provides a robust platform for managing and sharing complex neuroimaging data.
Semantic technologies enhance the accessibility and utility of distributed neuroscientific data.