A brain data integration model based on multiple ontology and semantic similarity

Authors:
Li Xue;Yun Xiong;Yangyong Zhu
Affiliations:
School of Computer Science, Fudan University, Shanghai, P.R. China;School of Computer Science, Fudan University, Shanghai, P.R. China;School of Computer Science, Fudan University, Shanghai, P.R. China
Venue:
BI'10 Proceedings of the 2010 international conference on Brain informatics
Year:
2010

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Abstract

In this paper, a brain data integration model(BDIM) is proposed by building up the Brain Science Ontology(BSO), which integrates the existing literature ontologies used in brain informatics research. Considering the features of current brain data sources, which are usually large scale, heterogeneous and distributed, our model offers brain scientists an effective way to share brain data, and helps them optimize the systematic management of those data. Besides, a brain data integration framework(BDIF) is presented in accordance with this model. Finally, many key issues about the brain data integration are also discussed, including semantic similarity computation, new data source insertion and the brain data extraction.