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Multi-level Big Data Content Services for Mental Health Care

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Abstract

Systematic brain informatics studies on mental health care produce various health big data of mental disorders and bring new requirements on the data acquisition and computing, from the data level to the information, knowledge and wisdom levels. Aiming at these challenges, this chapter proposes a brain and health big data center. A global content integrating mechanism and a content-oriented cloud service architecture are developed. The illustrative example demonstrates significance and usefulness of the proposed approach.

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Notes

  1. 1.

    Skowron et al. proposed “Wisdom = Interactions + Adaptive Judgement + Knowledge”. In the WaaS architecture, all of big data, from data to information and knowledge, are data resources for bringing “Wisdom”. Hence, we change “Knowledge” to “Data Contents” in this study.

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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), Research Supported by the CAS/SAFEA International Partnership Program for Creative Research Teams, Open Foundation of Key Laboratory of Multimedia and Intelligent Software (Beijing University of Technology), Beijing, the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (25330270), and Support Center for Advanced Telecommunications Technology Research, Foundation (SCAT), Japan.

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Correspondence to Ning Zhong .

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Chen, J. et al. (2016). Multi-level Big Data Content Services for Mental Health Care. In: Zhong, N., Ma, J., Liu, J., Huang, R., Tao, X. (eds) Wisdom Web of Things. Web Information Systems Engineering and Internet Technologies Book Series. Springer, Cham. https://doi.org/10.1007/978-3-319-44198-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-44198-6_7

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