Developing a Provenance Warehouse for the Systematic Brain Informatics Study

Jianhui Chen (), Ning Zhong and Jianhua Feng ()
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Jianhui Chen: International WIC Institute, Beijing University of Technology, Beijing 100124, P. R. China
Ning Zhong: International WIC Institute, Beijing University of Technology, Beijing 100124, P. R. China2Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi-City 371-0816, Japan
Jianhua Feng: Department of Computer Science and Technology, Tsinghua University, Beijing 100084, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2017, vol. 16, issue 06, 1581-1609

Abstract: Aiming at the unstructured brain data and data-driven research process, provenances have become an important component of brain and health big data rather than the accessory of raw experimental data in the systematic Brain Informatics (BI) study. However, the existing file-based or transaction-database-based provenance queries cannot effectively support quickly understanding data and generating decisions or suppositions in the systematic BI study, which need multi-aspect and multi-granularity provenance information and a process of incremental modification. Inspired by studies on the data warehouse and online analytical processing (OLAP) technology, this paper proposes a BI provenance warehouse. The provenance cube and basic OLAP operations are defined. A complete Data-Brain-based development approach is also designed. Such a BI provenance warehouse represents a radically new way for developing the brain big data center, which regards raw experimental data, provenances and domain ontologies as different levels of brain big data for data sharing and mining.

Keywords: Data-brain; provenances; data warehouse; online analytical processing; provenance cube (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1142/S0219622015500418

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