Abstract
The systematic Brain Informatics (BI) study is a data-driven process and all decision-making and suppositions depend on the deep understanding of brain data. Aiming at unstructured brain data, semantic neuroimaging data provenances, called BI provenances, have been constructed to support the quick and comprehensive understanding about data origins and data processing. However, the existing file-based or transaction-database-based provenance queries cannot effectively meet the requirements of understanding data and generating decision or suppositions in the systematic study, which needs multi-aspect and multi-granularity information of provenances. Inspired by the online analytical processing (OLAP) system, this paper proposes provenance cubes to support multi-aspect and multi-granularity provenance queries. A Data-Brain based approach is also designed to develop a BI OLAP system based on provenances cubes. The case study demonstrates significance and usefulness of the proposed approach.
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- 1.
As stated above, “1” means the lowest dimension level of information dimensions. In this Data-Brain driven data ETL, information dimensions are corresponding to sub-dimensions of the Data-Brain. Thus, the extracted provenance information is instances of the lowest level of dimensional members and has the corresponding dimension level “0”.
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Acknowledgments
The work is supported by National Basic Research Program of China (2014CB744600), China Postdoctoral Science Foundation (2013M540096), International Science & Technology Cooperation Program of China (2013DFA32180), National Natural Science Foundation of China (61272345), Open Foundation of Key Laboratory of Multimedia and Intelligent Software (Beijing University of Technology), Beijing.
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Chen, J., Feng, J., Zhong, N., Huang, Z. (2014). Constructing Provenance Cubes Based on Semantic Neuroimaging Data Provenances. In: Zhao, D., Du, J., Wang, H., Wang, P., Ji, D., Pan, J. (eds) The Semantic Web and Web Science. CSWS 2014. Communications in Computer and Information Science, vol 480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45495-4_19
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DOI: https://doi.org/10.1007/978-3-662-45495-4_19
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