Mapping Global Research Output in Big Data during 2007-16

S.M. Dhawan, Brij Mohan Gupta, Ritu Gupta


The paper examines global research in big data, as covered in Scopus database 2007-16, on a series of bibliometric indicators. The study finds that big data registered exceedingly fast growth (135.2%), but averaged low citation impact per paper (3.75) and accounted for very low share of highly cited papers (0.86%) in 10 years. The study reports publication trends in big data research by top countries, top institutions, top authors, top journals, major subject areas, publication modes, and country-level share of international collaborative publications. The study concludes that big data is a subject of recent origin. Given its major potential to impact business, governance, society, healthcare, industry and many other sectors, big data is fast emerging as a major discipline of interest and importance to nations, corporates, and institutions across developed and fast emerging economies.


Big Data Research; Global Publications; Scientometrics; Bibliometrics.


Big data in action: definition, value, evolutions, benefits and context.

What is Big Data Analytics?

Moorthy, M., Baby, R. & Senthamaraiselvi, S (2014). An Analysis for Big Data and its Technologies. International Journal of Computer Science Engineering and Technology (IJCSET), Vol 4, Issue 12, 412-418.

Halevi, Gali and Moed, Henk F. (2012). The Evolution of Big Data as a Research and Scientific Topic: Overview of the Literature. Research Trends (Special Issue), 3-6.

Singh, V.K., Banshal, S.K., Singhal, K. et al. Scientometric mapping of research on ‘Big Data’. Scientometrics (2015) 105: 727-741.

Singh, Punit Kumar and Singh, Ajay P. Diffusion of Big Data in Indian Scientific Literature: Study of Research Productivity and Scientific Collaboration. Library Philosophy and Practice (e-journal) (2017).

Mathisen, B.M., Roman, D., & Wienhofen, L.W. (2015). Empirical Big Data Research: A Systematic Literature Mapping. Information Systems arXiv:1509.03045 [cs.DL]

Porter, A.L. Hunag, Y, Schuehle, Y and Youtie, Jan. Meta data: Big data research evolving across disciplines, players, and topics. Conference Paper. June 2015 DOI: 10.1109/BigDataCongress.2015.44.

Mathisen, B.M., Roman, D., & Wienhofen, L.W. (2015). Empirical Big Data Research: A Systematic Literature Mapping. Information Systems arXiv:1509.03045 [cs.DL]

Kalantari, A., Kamsin, A., Kamaruddin, H.S. et al. (2017). A bibliometric approach to tracking big data research trends. J Big Data (2017) 4: 30.

Liao, Huchang, Ming Tang, Li Luo, Chunyang Li, Francisco Chiclana, and Xiao-Jun Zeng. “A Bibliometric Analysis and Visualization of Medical Big Data Research.” Sustainability 10, no. 2 (January 11, 2018): 166. doi:10.3390/su10010166.

Gua, Dongxiao, Lia, Jingjing, Lia, Xingguo, Lianga, Changyong., 2017, Visualizing the knowledge structure and evolution of big data research in healthcare informatics. International Journal of Medical Informatics February 2017, 98, 22-32.

Youtie, Jan, Porter, Alan L and Huang, Ying. 2017, Early social science research about big data. Science and Public Policy 1 February 2017, 44(1), 65-74.

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DOI: 10.28991/esj-2018-01135


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