Sym(p)hony: Towards a dynamic neuroscience information system.
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1
Brain Mind Institute - EPFL, Switzerland
Purpose: There are currently two popular approaches of information access to neuroscientists. 1) Keyword-based searches of unstructured information. Which allows a retrieval of data based on lexicographical properties. 2) Retrieval of information based on structured systems, represented by some controlled terms/classes (e.g. through an ontology). Both methods are effective, however in the neuroscience domain both are unable to capture the information in a sufficient manner, especially due to the dynamic nature of neuroscience knowledge generation. The overlaps between both methods make up only a small area of neuroscience and are not effective at using the strengths that each approach has to offer. Sym(p)hony is a hybrid system, which tries to mend this gap by showing how a computer-aided, systematic evolution of an ontology may be possible, using elements of both approaches.
Method: Sym(p)ony is build on two pillars: 1) elements (which are instances of classes) and 2) relations (which are instances of relationships) between them. The first iteration of the ontology used in the system is based on our current understanding of established classes and relationships that they have to one another. An expansion of classes and relationships is achieved by doing frequency searches of tokens of elements in literature. This process allows the generation of suggestions for classes and relationships, which are lacking from the previous iteration and could be included in a subsequent version.
Results: A first prototype has been implemented that demonstrates the ability of starting from an ontology (based on relationships, which can be reasoned on, and elements, found in neuroscience) that can be augmented based on new elements and relationships. These suggestions are generated from frequency analysis of a subset of the available neuroscience literature.
Conclusion: We present a system that facilitates the maintenance and computer-aided growth of an ontology, which takes the occurrence of new elements and concepts into account by analyzing the frequency with which they occur in the present literature. This offers a possible approach to solve the problem in neuroscience, in which the integration of new concepts and elements lags significantly behind compared to when they become available in the unstructured domain.
Conference:
Neuroinformatics 2010 , Kobe, Japan, 30 Aug - 1 Sep, 2010.
Presentation Type:
Poster Presentation
Topic:
General neuroinformatics
Citation:
Telefont
M,
Muller
E,
Schürmann
F,
Hill
SL and
Markram
H
(2010). Sym(p)hony: Towards a dynamic neuroscience information system..
Front. Neurosci.
Conference Abstract:
Neuroinformatics 2010 .
doi: 10.3389/conf.fnins.2010.13.00069
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Received:
11 Jun 2010;
Published Online:
11 Jun 2010.
*
Correspondence:
Dr. Martin Telefont, Brain Mind Institute - EPFL, Lausanne, Switzerland, martin.telefont@epfl.ch