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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 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.
187 publications referenced in ScienceDirect contain the term Big Data in their titles.
References
Gantz, J., Reinsel, D.: Extracting value from chaos. IDC iView, pp 1–12 (2011)
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)
Intel IT Center: Planning Guide: Getting Started with Hadoop, Steps IT Managers Can Take to Move Forward with Big Data Analytics (2012)
Davenport, T., Barth, P.: Bean, R: How Big Data is different. MIT Sloan Mgt Rev. 54(1), 43–46 (2012)
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)
Team, O.R.: Big Data Now: Current Perspectives from O’Reilly Radar. O’Reilly Media, Sebastopol (2011)
Grobelnik, M.: Big Data Tutorial. http://videolectures.net/eswc2012_grobelnik_big_data/
Laney D.: 3-D data management: controlling data volume, velocity and variety. META Group Research Note (2001)
Sagiroglu, S., Sinanc, D.: Big data: a review. In: IEEE International Conference on CTS (2013)
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)
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw Appl 19, 171–209 (2014)
Zhu, Y.Q., Chen, H.G.: Social media and human need satisfaction: Implications for social media marketing. Bus. Horiz. 58, 335–345 (2015)
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
Mangold, W.G., Faulds, D.J.: Social media: the new hybrid element of the promotion mix. Bus. Horiz. 52(4), 357–365 (2009)
Gallup: The myth of social media. http://online.wsj.com/public/resources/documents/sac_report_11_socialmedia_061114.pdf. Accessed 3 July 2014
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)
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)
O’Leary, D.: Exploiting Big Data from mobile device sensor-based apps: challenges and benefits. MIS Q. Executive 12(4), 179 (2014)
Laurila, J.K., Gatica-Perez, D., Aad, I., Blom, J., Bornet, O.: Pervasive and Mobile Computing, vol. 9, pp. 752–777 (2013)
Gonzalez, M.C., Hidalgo, C.A., Barabasi, A.L.: Understanding individual human mobility patterns. Nat. 4, 53–779 (2008)
Bellavista, P., Montanari, R., Das, S.K.: Mobile social networking middleware: a survey. Pervasive Mob. Comput. 9, 437–453 (2013)
Kambatla, K., Kollias, G., Kumar, V., Grama, A.: Trends in Big Data analytics. J. Parallel Distrib. Comput. 74, 2561–2573 (2014)
Gandomi, A., Haider, M.: Beyond the hype: Big Data concepts, methods, and analytics. Int. J. Inf. Manage. 35, 137–144 (2015)
Labrinidis, A., Jagadish, H.V.: Challenges and opportunities with Big Data. Proc VLDB Endowment 5(12), 2032–2033 (2012)
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)
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)
Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54, 2787–2805 (2010)
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)
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)
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)
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)
March, S.T., Smith, G.F.: Design and natural science research on information technology. Decis. Support Syst. 15(4), 251–266 (1995)
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)
Bizer, C., Boncz, P., Brodie, M.L., Erling, O.: The meaningful use of Big Data: four perspectives. SIGMOD 40(4), 56–60 (2011)
Jacobs, A.: The pathologies of Big Data. Commun. ACM 52(8), 36 (2009)
Madden, S.: From databases to Big Data. IEEE Comput. 16(3), 4–6 (2012)
Goes, P.B.: Big Data and IS research methods. MIS Q. 38(3), 3–8 (2014)
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)
Pospiech, M., Felden, C.: Big Data: a state-of-the-art. In: Americas Conference on Information Systems (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-25747-1_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25746-4
Online ISBN: 978-3-319-25747-1
eBook Packages: Computer ScienceComputer Science (R0)