Building a Data‐mining Grid for Multiple Human Brain Data Analysis

Abstract

E-science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain-informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data-mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long-term, global field of vision.

Web Intelligence Meets Brain Informatics

“…It attempts to understand human intelligence in depth, towards a holistic view at a long-term, global vision to understand the principles and mechanisms of human information processing system (HIPS), with respect to functions from perception to thinking, such as multi-perception, attention, memory, language, computation, heuristic search, reasoning, planning, decision-making, problem-solving, learning, discovery and creativity. BI can be regarded as brain science in WI centric IT age [98,99]. BI is proposing to study human brain from the viewpoint of informatics (i.e., human brain is an information processing system) and use informatics (i.e., WI centric information technology) to support brain science study.…”

“…In this vision, new kinds of BI methods and global research communities will emerge, through infrastructure on the wisdom Web and knowledge grids that enables high speed and distributed, large-scale analysis and computations, and radically new ways of sharing data/knowledge. On the other hand, some of these lessons in cognitive science and neuroscience are applicable to novel technological developments in BI, yet others may need to be enhanced or transformed in order to manage and account for the complex and possibly more innovative practices of sharing data/knowledge that are made technically possible by the wisdom Web and knowledge grids [37,38,98].…”

“…The first aspect means that WI technologies provide an agent based multidatabase mining grid architecture on the wisdom Web for building a braininformatics portal [95,98]. A conceptual model with three levels of workflows, corresponding to a grid with three layers, namely data-grid, mining-grid, and knowledge-grid, respectively, is utilized to manage, represent, integrate, analyze, and utilize the information coming from multiple, huge data and knowledge sources.…”

“…It offers a systematic approach for measuring, collecting, modeling, transforming, managing, and mining multiple human brain data obtained from various cognitive experiments by using fMRI and EEG [96,98].…”

Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

“…Advances in high performance computing, computational grid and cloud computing platforms are enabling researchers to explore increasingly computationally complex problems in domains such as chemistry, meteorology, high-energy physics, astronomy, biology, human brain planning and sensor networks [31,24,62,5,23]. A key consideration when developing applications for these platforms is how to schedule application tasks in order to optimize performance with respect to the available resources.…”