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Research on Big Data

Characterizing the Field and Its Dimensions

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Advances in Conceptual Modeling (ER 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9382))

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Abstract

Big Data has emerged as a significant area of study for both practitioners and researchers. Big Data is a term for massive data sets with large structure. In 2012, Big Data passed the top of the Gartner Hype Cycle, attesting the maturity level of this technology and its applications. The aim of this paper is to examine whether the Big Data research community reached the same level of maturity. For this purpose, we provide a framework identifying existing and emerging research areas of Big Data. This framework is based on five dimensions, including the SMACIT perspective. Current and past research in Big Data are analyzed using a bibliometric study of publications based on more than a decade of related academic publications. The results have shown that even if significant contributions have been made by the research community, attested by a continuous increase in the number of scientific publications that address Big Data, it lags behind entreprises’ expectations.

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Notes

  1. 1.

    http://www.emc.com/leadership/digital-universe/2014iview/index.htm.

  2. 2.

     http://strata.oreilly.com/2010/01/roger-magoulas-on-big-data.html.

  3. 3.

    One paper published in 1987 mentions big data in its abstract. However it is not linked to the modern understanding of the concept.

  4. 4.

    187 publications referenced in ScienceDirect contain the term Big Data in their titles.

References

  1. Gantz, J., Reinsel, D.: Extracting value from chaos. IDC iView, pp 1–12 (2011)

    Google Scholar 

  2. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., et al.: Big Data: the next frontier for innovation, competition, and productivity. McKinsey Global Institute (2011)

    Google Scholar 

  3. Intel IT Center: Planning Guide: Getting Started with Hadoop, Steps IT Managers Can Take to Move Forward with Big Data Analytics (2012)

    Google Scholar 

  4. Davenport, T., Barth, P.: Bean, R: How Big Data is different. MIT Sloan Mgt Rev. 54(1), 43–46 (2012)

    Google Scholar 

  5. Jin, X., Wah, B.W., Cheng, X., Wang, Y.: Significance and challenges of Big Data research. J. Big Data Res. 2(2), 59–64 (2015)

    Article  Google Scholar 

  6. Team, O.R.: Big Data Now: Current Perspectives from O’Reilly Radar. O’Reilly Media, Sebastopol (2011)

    Google Scholar 

  7. Grobelnik, M.: Big Data Tutorial. http://videolectures.net/eswc2012_grobelnik_big_data/

  8. Laney D.: 3-D data management: controlling data volume, velocity and variety. META Group Research Note (2001)

    Google Scholar 

  9. Sagiroglu, S., Sinanc, D.: Big data: a review. In: IEEE International Conference on CTS (2013)

    Google Scholar 

  10. Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from Big Data to big impact. MIS Q. 36(4), 1165–1188 (2012)

    Google Scholar 

  11. Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw Appl 19, 171–209 (2014)

    Article  MathSciNet  Google Scholar 

  12. Zhu, Y.Q., Chen, H.G.: Social media and human need satisfaction: Implications for social media marketing. Bus. Horiz. 58, 335–345 (2015)

    Article  Google Scholar 

  13. ComScore. It’s a social world: Top 10 need-to-knows about social networking and where it’s headed. http://www.comscore.com/. Accessed 10 May 2013

  14. Mangold, W.G., Faulds, D.J.: Social media: the new hybrid element of the promotion mix. Bus. Horiz. 52(4), 357–365 (2009)

    Article  Google Scholar 

  15. Gallup: The myth of social media. http://online.wsj.com/public/resources/documents/sac_report_11_socialmedia_061114.pdf. Accessed 3 July 2014

  16. Irfan, R., Bickler, G., Khan, S.U., Kolodziej, J., Li, H., Chen, D., Wang, L., Hayat, K., Madani, S.A., Nazir, B., Khan, I.A., Ranjan, R.: Survey on social networking services. IET Netw. 2(4), 224–234 (2013)

    Article  Google Scholar 

  17. King, I., Li, J., Chan, K.T.: A Brief Survey of Computational Approaches in Social Computing. In: Proceedings of International Joint Conference Neural Networks, Atlanta, Georgia, USA (2009)

    Google Scholar 

  18. O’Leary, D.: Exploiting Big Data from mobile device sensor-based apps: challenges and benefits. MIS Q. Executive 12(4), 179 (2014)

    Google Scholar 

  19. Laurila, J.K., Gatica-Perez, D., Aad, I., Blom, J., Bornet, O.: Pervasive and Mobile Computing, vol. 9, pp. 752–777 (2013)

    Google Scholar 

  20. Gonzalez, M.C., Hidalgo, C.A., Barabasi, A.L.: Understanding individual human mobility patterns. Nat. 4, 53–779 (2008)

    Google Scholar 

  21. Bellavista, P., Montanari, R., Das, S.K.: Mobile social networking middleware: a survey. Pervasive Mob. Comput. 9, 437–453 (2013)

    Article  Google Scholar 

  22. Kambatla, K., Kollias, G., Kumar, V., Grama, A.: Trends in Big Data analytics. J. Parallel Distrib. Comput. 74, 2561–2573 (2014)

    Article  Google Scholar 

  23. Gandomi, A., Haider, M.: Beyond the hype: Big Data concepts, methods, and analytics. Int. J. Inf. Manage. 35, 137–144 (2015)

    Article  Google Scholar 

  24. Labrinidis, A., Jagadish, H.V.: Challenges and opportunities with Big Data. Proc VLDB Endowment 5(12), 2032–2033 (2012)

    Article  Google Scholar 

  25. Polash, F., Abuhussein, A., Shiva, S.: A Survey of Cloud Computing Taxonomies: Rationale and Overview. In: 9th International Conference on Internet Technology and Secured Transactions (2014)

    Google Scholar 

  26. Assunçao, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A.S., Buyya, R.: Big Data computing and clouds: Trends and future directions. J. Parallel Distrib. Comput. 79–80, 3–15 (2015)

    Article  Google Scholar 

  27. Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54, 2787–2805 (2010)

    Article  MATH  Google Scholar 

  28. Perera, C., Liu, C.H., Jayawardena, S., Chen, M.: A survey on internet of things from industrial market perspective. IEEE Access 2, 1660–1679 (2015)

    Article  Google Scholar 

  29. Chen, M., Mao, S., Zhang, Y., Leung, V.C.M.: Big Data : Related Technologies. Challenges and Future Prospects. SpringerBriefs in Computer Science. Springer, Cambridge (2014)

    Book  Google Scholar 

  30. Agrawal D, Bernstein P, Bertino E, Davidson S, Dayal U, Franklin M, Gehrke J, Haas L, Halevy A, Han J et al.: Challenges and opportunities with Big Data. A community white paper developed by researches across the United States (2012)

    Google Scholar 

  31. Prat, N., Comyn-Wattiau, I., Akoka, J.: Artifact evaluation in information systems design science research – a holistic view. In: PACIS 2014 Proceedings, Paper 23 (2014)

    Google Scholar 

  32. March, S.T., Smith, G.F.: Design and natural science research on information technology. Decis. Support Syst. 15(4), 251–266 (1995)

    Article  Google Scholar 

  33. Cuzzocrea, A., Song, I.Y., Davis, K.: Analytics over large-scale multidimensional data: the Big Data revolution. In: Proceedings of the ACM 14th International Workshop on Data Warehousing and OLAP, pp. 101–103. ACM, New York, USA (2011)

    Google Scholar 

  34. Bizer, C., Boncz, P., Brodie, M.L., Erling, O.: The meaningful use of Big Data: four perspectives. SIGMOD 40(4), 56–60 (2011)

    Article  Google Scholar 

  35. Jacobs, A.: The pathologies of Big Data. Commun. ACM 52(8), 36 (2009)

    Article  Google Scholar 

  36. Madden, S.: From databases to Big Data. IEEE Comput. 16(3), 4–6 (2012)

    Article  Google Scholar 

  37. Goes, P.B.: Big Data and IS research methods. MIS Q. 38(3), 3–8 (2014)

    Google Scholar 

  38. Hansmann, T., Niemeyer, P.: Big Data - characterizing an emerging research field using topic models. In: IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) (2014)

    Google Scholar 

  39. Pospiech, M., Felden, C.: Big Data: a state-of-the-art. In: Americas Conference on Information Systems (2012)

    Google Scholar 

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Correspondence to Jacky Akoka .

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Akoka, J., Comyn-Wattiau, I., Laoufi, N. (2015). Research on Big Data. In: Jeusfeld, M., Karlapalem, K. (eds) Advances in Conceptual Modeling. ER 2015. Lecture Notes in Computer Science(), vol 9382. Springer, Cham. https://doi.org/10.1007/978-3-319-25747-1_18

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  • DOI: https://doi.org/10.1007/978-3-319-25747-1_18

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-25747-1

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