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Multi-level Big Data Content Services for Mental Health Care

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Wisdom Web of Things

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.

Author information

Authors and Affiliations

  1. The International WIC Institute, Beijing University of Technology, Beijing, China

    Jianhui Chen, Jian Han, Han Zhong, Ningning Wang, Youjun Li, Zhijiang Wan & Dongsheng Wang

  2. The Industry Innovation Center for Web Intelligence, Suzhou, China

    Yue Deng

  3. The Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi-city, 371-0816, Japan

    Zhijiang Wan, Taihei Kotake & Ning Zhong

  4. Institute of Intelligent Transport System, School of Computer Science and Engineering, Jiangsu University of Science of Technology, Zhenjiang, China

    Dongsheng Wang

  5. Faculty of Health, Engineering and Sciences, The University of Southern Queensland, Toowoomba, Australia

    Xiaohui Tao

  6. Beijing Advanced Innovation Center for Future Internet Technology, The International WIC Institute, Beijing University of Technology, Beijing, China

    Ning Zhong

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  1. Jianhui Chen
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  11. Ning Zhong
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Correspondence to Ning Zhong .

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Editors and Affiliations

  1. Dep of Life Sci & Informatic, Maebashi Institute of Technology Dep of Life Sci & Informatic, Maebashi, Japan

    Ning Zhong

  2. Faculty of Computer and Information Sciences, Hosei University, Tokyo, Japan

    Jianhua Ma

  3. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  4. Faculty of Computer and Information Science, Hosei University , Tokyo, Japan

    Runhe Huang

  5. Department of Mathematics and Computing, The University of Southern Queensland, Toowoomba, Queensland, Australia

    Xiaohui Tao

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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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