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Big Data Architecture and Reference Models

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11231))

Abstract

The emergence of big data provides opportunities for both academic and industrial area and changes the way people solve complex problems and evaluate the value of data. However, there is a lack of studies on architecture frameworks and modelling methods in the context of big data, which is the key to support the analysis, design, implementation and evaluation phases of big data applications. The paper proposes a Big Data Architecture (BDA) to support the top-level design of enterprise information integration applications in big data environments. Moreover, reference models of performance, business, application, data, infrastructure and security views are discussed.

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References

  1. Kitchin, R.: Big data, new epistemologies and paradigm shifts. Big Data Soc. 1(1) (2014). https://doi.org/10.1177/2053951714528481

    Article  Google Scholar 

  2. Lohr, S.: The age of big data. New York Times 11(2012) (2012)

    Google Scholar 

  3. NBD-PWG, et al.: NIST big data interoperability framework, pp. 1500–1506. Special Publication (2015)

    Google Scholar 

  4. China electronic technology standardization research institute. White paper on big data standardization (2018). http://www.cesi.cn/201803/3709.html

  5. Kaisler, S., Armour, F., Espinosa, J.A., et al.: Big data: issues and challenges moving forward. In: 2013 46th Hawaii International Conference on System Sciences (HICSS), pp. 995–1004. IEEE (2013)

    Google Scholar 

  6. Katal, A., Wazid, M., Goudar, R.: Big data: issues, challenges, tools and good practices. In: 2013 Sixth International Conference on Contemporary Computing (IC3), pp. 404–409. IEEE (2013)

    Google Scholar 

  7. Boyd, D., Crawford, K.: Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Inf. Commun. Soc. 15(5), 662–679 (2012)

    Article  Google Scholar 

  8. Crawford, K., et al.: Six provocations for big data (2011)

    Google Scholar 

  9. Jacobs, A.: The pathologies of big data. Commun. ACM 52(8), 36–44 (2009)

    Article  Google Scholar 

  10. Michael, K., Miller, K.W.: Big data: new opportunities and new challenges [guest editors’ introduction]. Computer 46(6), 22–24 (2013)

    Article  Google Scholar 

  11. Blanchard, B.S., Fabrycky, W.J., Fabrycky, W.J.: Systems Engineering and Analysis, vol. 4. Prentice Hall, Englewood Cliffs (1990)

    Google Scholar 

  12. Ramos, A.L., Ferreira, J.V., Barceló, J.: Model-based systems engineering: an emerging approach for modern systems. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 42(1), 101–111 (2012)

    Article  Google Scholar 

  13. Shah, H., El Kourdi, M.: Frameworks for enterprise architecture. IT Professional 9(5) (2007)

    Article  Google Scholar 

  14. Crawley, E., De Weck, O., Magee, C., et al.: The influence of architecture in engineering systems (monograph). Citeseer (2004)

    Google Scholar 

  15. McAfee, A., Brynjolfsson, E., Davenport, T.H., et al.: Big data: the management revolution. Harvard Bus. Rev. 90(10), 60–68 (2012)

    Google Scholar 

  16. Russom, P., et al.: Big data analytics. TDWI Best Practices report, fourth quarter, vol. 19, no. 4, pp. 1–34 (2011)

    Google Scholar 

  17. Armbrust, M., Fox, A., Griffith, R., et al.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Article  Google Scholar 

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Acknowledgements

This work is sponsored by the National Natural Science Foundation of China, No. 61174168 and 61771281, the 2018 Industrial Internet innovation and development project.

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Correspondence to Qing Li .

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Li, Q. et al. (2019). Big Data Architecture and Reference Models. In: Debruyne, C., Panetto, H., Guédria, W., Bollen, P., Ciuciu, I., Meersman, R. (eds) On the Move to Meaningful Internet Systems: OTM 2018 Workshops. OTM 2018. Lecture Notes in Computer Science(), vol 11231. Springer, Cham. https://doi.org/10.1007/978-3-030-11683-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-11683-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11682-8

  • Online ISBN: 978-3-030-11683-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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