Advertisement

WaaS—Wisdom as a Service

  • Jianhui Chen
  • Jianhua Ma
  • Ning ZhongEmail author
  • Yiyu Yao
  • Jiming Liu
  • Runhe Huang
  • Wenbin Li
  • Zhisheng Huang
  • Yang Gao
Chapter
Part of the Web Information Systems Engineering and Internet Technologies Book Series book series (WISE)

Abstract

An emerging hyper-world encompasses all human activities in a social-cyber-physical space. Its power derives from the Wisdom Web of Things (W2T) cycle, namely, “from things to data, information, knowledge, wisdom, services, humans, and then back to things.” The W2T cycle leads to a harmonious symbiosis among humans, computers and things, which can be constructed by large-scale converging of intelligent information technology applications with an open and interoperable architecture. The recent advances in cloud computing, the Internet/Web of Things, big data and other research fields have provided just such an open system architecture with resource sharing/services. The next step is therefore to develop an open and interoperable content architecture with intelligence sharing/services for the organization and transformation in the “data, information, knowledge and wisdom (DIKW)” hierarchy. This chapter introduces Wisdom as a Service (WaaS) as a content architecture based on the “paying only for what you use” IT business trend. The WaaS infrastructure, WaaS economics, and the main challenges in WaaS research and applications are discussed. A case study is described to demonstrate the usefulness and significance of WaaS. Relying on the clouds (cloud computing), things (Internet of Things) and big data, WaaS provides a practical approach to realize the W2T cycle in the hyper-world for the coming age of ubiquitous intelligent IT applications.

Keywords

Cloud Computing Mobile Internet Cloud Computing Platform Data Transmission Protocol Content Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The work is supported by National Key Basic Research Program of China (2014CB744605), 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, the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (25330270).

References

  1. 1.
    International Telecommunication Union (ITU), The World in 2013: ICT Facts and Figures, http://www.itu.int/ITU-D/ict/facts/material/ICTFactsFigures2013.pdf. Accessed 27 Feb 2013
  2. 2.
    L. Atzori, A. Iera, G. Morabito, The internet of things: a survey. Comput. Netw. 54, 27872805 (2010)CrossRefzbMATHGoogle Scholar
  3. 3.
    J.H. Ma, R.H. Huang, Improving human interaction with a hyperworld, in Proceedings of the Pacific Workshop on Distributed Multimedia Systems (DMS96) (1996), pp. 46–50Google Scholar
  4. 4.
    N. Zhong, J.H. Ma, R.H. Huang, J.M. Liu, Y.Y. Yao, Y.X. Zhang, J.H. Chen, Research challenges and perspectives on wisdom web of things (W2T). J. Supercomput. 64(3), 862882 (2013)CrossRefGoogle Scholar
  5. 5.
    J.H. Ma, Smart u-things challenging real world complexity, in IPSJ Symposium Series (2005), pp. 146–150Google Scholar
  6. 6.
    S. Lohr, The age of big data (New York Times, 2012)Google Scholar
  7. 7.
    D. Howe, M. Costanzo, P. Fey, T. Gojobori, L. Hannick, W. Hide, D.P. Hill, R. Kania, M. Schaeffer, S. St. Pierre, S. Twigger, O. White, S.Y. Rhee, Big data: the future of biocuration. Nature 455, 4750 (2008)CrossRefGoogle Scholar
  8. 8.
    N.B. Turk-Browne, Functional interactions as big data in the human brain. Science 342(6158), 580–584 (2013)CrossRefGoogle Scholar
  9. 9.
    Q.P. Zhang, Z. Feng, F.Y. Wang, D. Zeng, Modeling cyber-enabled crowd-powered search, in The Second Chinese Conference on Social Computing, Beijing (2010)Google Scholar
  10. 10.
    Q.P. Zhang, F.Y. Wang, D. Zeng, T. Wang, Understanding crowd-powered search groups: a social network perspective. PLoS ONE 7(6), e39749 (2012). doi: 10.1371/journal.pone.0039749 MathSciNetCrossRefGoogle Scholar
  11. 11.
    N. Zhong, J.M. Liu, Y.Y. Yao, S. Ohsuga, Web intelligence (WI), in Proceedings of the 24th IEEE Computer Society International Computer Software and Applications Conference (COMPSAC 2000) (2000), pp. 469–470Google Scholar
  12. 12.
    N. Zhong, J.M. Liu, Y.Y. Yao, In search of the wisdom web. IEEE Comput. 35(11), 27–31 (2002)CrossRefGoogle Scholar
  13. 13.
    N. Zhong, Towards web intelligence, in E. Menasalvas Ruiz, J. Segovia, P.S. Szczepaniak (eds.), Advances in Web Intelligence, LNAI 2663 (Springer, 2003), pp. 1–14Google Scholar
  14. 14.
    N. Zhong, J. Liu, Y.Y. Yao, Envisioning intelligent information technologies through the prism of web intelligence. Commun. ACM 50(3), 8994 (2007)CrossRefGoogle Scholar
  15. 15.
    N. Zhong, J.M. Liu, Y.Y. Yao, Web intelligence (WI), in The Encyclopedia of Computer Science and Engineering, vol. 5 (Wiley, 2009), pp. 3062–3072Google Scholar
  16. 16.
    J.M. Liu, Web intelligence (WI): what makes wisdom web? in Proceedings the 18th International Joint Conference on Artificial Intelligence (IJCAI’03) (2003), pp. 1596–1601Google Scholar
  17. 17.
    J.M. Liu, N. Zhong, Y.Y. Yao, Z.W. Ras, The wisdom web: new challenges for web intelligence (WI). J. Intell. Inf. Syst. 20(1), 59 (2003)CrossRefGoogle Scholar
  18. 18.
    D. Guinard, V. Trifa, F. Mattern, E. Wilde, From the internet of things to the web of things: resource-oriented architecture and best practices, in Architecting the Internet of Things (Springer, 2011), pp. 97–129Google Scholar
  19. 19.
    M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, M. Zaharia, A view of cloud computing. Commun. ACM 53(4), 5058 (2010)CrossRefGoogle Scholar
  20. 20.
    R.L. Ackoff, From data to wisdom. J. Appl. Syst. Anal. 16, 39 (1989)Google Scholar
  21. 21.
    N. Zhong, J.M. Liu, Y.Y. Yao, J.L. Wu, S.F. Lu (eds.) Web Intelligence Meets Brain Informatics, State-of-the-Art-Survey (Springer LNCS 4845, 2007)Google Scholar
  22. 22.
  23. 23.
    Y.Y. Yao, Y. Zeng, N. Zhong, X.J. Huang, Knowledge retrieval (KR), in Proceedings of the 2007 IEEE/WIC/ACM International Conference on Web Intelligence (WI’07) (2007), pp. 729–735Google Scholar
  24. 24.
    G.B. Zou, B.F. Zhang, J.X. Zheng, Y.S. Li, J.H. Ma, MaaS: model as a service in cloud computing and cyber-I space, in Proceedings of the 12th IEEE International Conference on Computer and Information Technology (CIT2012) (2012), pp. 1125–1130Google Scholar
  25. 25.
    Y.Y. Yao, Web intelligence: new frontiers of exploration, in Proceedings of 2005 International Conference on Active Media Technology (AMT 2005) (2005), pp. 3–8Google Scholar
  26. 26.
    J.H. Ma, J. Wen, R.H. Huang, B.X. Huang, Cyber-individual meets brain informatics. IEEE Intell. Syst. 26(5), 3037 (2011)CrossRefGoogle Scholar
  27. 27.
    H.U. Wittchen, F. Jacobi, J. Rehm, A. Gustavsson, M. Svensson, B. Jansson, J. Olesen, C. Allgulander, J. Alonso, C. Faravelli, L. Fratiglioni, P. Jennum, R. Lieb, A. Maercker, J. van Os, M. Preisig, L. Salvador-Carulla, R. Simon, H.-C. Steinhausen, The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur. Neuropsychopharm. 21(9), 655679 (2011)CrossRefGoogle Scholar
  28. 28.
    N. Zhong, S. Motomura, Agent-enriched data mining: a case study in brain informatics. IEEE Intell. Syst. 24(3), 3845 (2009)CrossRefGoogle Scholar
  29. 29.
    J.H. Chen, N. Zhong, Toward the data-brain driven systematic brain data analysis. IEEE Trans. Syst. Man Cybernet. Syst. 43(1), 222228 (2013)MathSciNetGoogle Scholar
  30. 30.
    D. Fensel, F. van Harmelen, B. Andersson, P. Brennan, H. Cunningham, E. Della Valle, F. Fischer, Z.S. Huang, A. Kiryakov, T.K.-i. Lee, L. Schooler, V. Tresp, S. Wesner, M. Witbrock, N. Zhong, Towards LarKC: a platform for web-scale reasoning, in Proceedings of the 2nd IEEE International Conference on Semantic Computing (ICSC08) (2008), pp. 524–529Google Scholar
  31. 31.
    N. Zhong, J.M. Bradshaw, J.M. Liu, J.G. Taylor, Brain informatics, Special Issue on Brain Informatics. IEEE Intell. Syst. 26(5), 16–21 (2011)Google Scholar
  32. 32.
    N. Zhong, J.H. Chen, Constructing a new-style conceptual model of brain data for systematic brain informatics. IEEE Trans. Knowl. Data Eng. 24(12), 21272142 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jianhui Chen
    • 1
  • Jianhua Ma
    • 2
  • Ning Zhong
    • 3
    • 4
    Email author
  • Yiyu Yao
    • 5
    • 6
  • Jiming Liu
    • 5
    • 7
  • Runhe Huang
    • 8
  • Wenbin Li
    • 9
  • Zhisheng Huang
    • 5
    • 10
  • Yang Gao
    • 11
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina
  2. 2.Faculty of Computer and Information SciencesHosei UniversityTokyoJapan
  3. 3.Department of Life Science and InformaticsMaebashi Institute of TechnologyMaebashi-cityChina
  4. 4.Beijing Advanced Innovation Center for Future Internet Technology, The International WIC InstituteBeijing University of TechnologyBeijingChina
  5. 5.International WIC InstituteBeijing University of TechnologyBeijingChina
  6. 6.Department of Computer ScienceUniversity of ReginaReginaCanada
  7. 7.Department of Computer ScienceHong Kong Baptist UniversityKowloon TongHong Kong SAR
  8. 8.Faculty of Computer and Information SciencesHosei UniversityTokyoJapan
  9. 9.Department of Computer ScienceShijiazhuang University of EconomicsShijiazhuangChina
  10. 10.Department of Computer ScienceVrije University AmsterdamAmsterdamThe Netherlands
  11. 11.Department of Computer ScienceNanjing UniversityNanjingChina

Personalised recommendations