Abstract
We extended the big data body of knowledge by analyzing the longitudinal literature to highlight important research topics and identify critical gaps. We initially collected 79,012 articles from 1900 to 2016 related to big data. We refined our sample to 13,029 articles allowing us to determine that the big data paradigm commenced in late 2011 and the research production exponentially rose starting in 2012, which approximated a Weibull distribution that captured 82% of the variance (\(p<.01\)). We developed a dominant topic list for the big data body of knowledge that contained 49 keywords resulting in an inter-rater reliability of 93% (\(\hbox {r}^{2}=0.89\)). We found there were 13 dominant topics that captured 49% of the big data production in journals during 2011–2016 but privacy and security related topics accounted for only 2% of those outcomes. We analyzed the content of 970 journal manuscripts produced during the first of 2016 to determine the current status of big data research. The results revealed a vastly different current trend with too many literature reviews and conceptual papers that accounted for 41% of the current big data knowledge production. Interestingly, we observed new big data topics emerging from the healthcare and physical sciences disciplines.
Similar content being viewed by others
References
Chen M, Mao S, Zhang Y, Leung VC (2014) Open issues and outlook in big data. In: Chen (ed) Big data: related technologies, challenges and future prospects, vol 1. Springer, New York, pp 81–89
Goldfield NI (2014) Big data–hype and promise. J Ambul Care Manag 37(3):195–196
Kambatla K, Kollias G, Kumar V, Grama A (2014) Trends in big data analytics. J Parallel Distrib Comput 74(7):2561–2573
Kim G-H, Trimi S, Chung J-H (2014) Big data applications in the public sector. Commun ACM 57(3):78–85. doi:10.1145/2500873
Pence HE (2015) What is big data and why is it important? J Educ Technol Syst 43(2):159–171. http://journals.sagepub.com/doi/abs/10.2190/ET.43.2.d
Bohannon J (2015) Credit card study blows holes in anonymity. Science 347(6221):468
De Zwart M, Humphreys S, Van Dissel B (2014) Surveillance, big data and democracy: lessons for Australia from the US and UK. Univ N South Wales Law J 37(2):713–747
Eastin MS, Brinson NH, Doorey A, Wilcox G (2016) Living in a big data world: predicting mobile commerce activity through privacy concerns. Comput Hum Behav 58:214–220
Ekbia H, Mattioli M, Kouper I, Arave G, Ghazinejad A, Bowman T, Suri VR, Tsou A, Weingart S, Sugimoto CR (2015) Big data, bigger dilemmas: a critical review. J Assoc Inf Sci Technol 66(8):1523–1545
Gharabaghi K, Anderson-Nathe B (2014) Big data for child and youth services? Child Youth Services, pp 193–195
Kshetri N (2014) Big datas impact on privacy, security and consumer welfar. Telecommun Policy 38(11):1134–1145
Lichtblau E, Weilandaug N (2016) Hacker releases more democratic party files, renewing fears of Russian Meddling. New York Times, New York
Dana M (2012) On Orbitz, Mac users steered to pricier hotels. Wall Streat J 1–3. http://www.wsj.com/articles/SB10001424052702304458604577488822667325882
Duhigg C (2014) The power of habit: why we do what we do in life and business. Penguin Random House, New York City
Filkins BL, Kim JY, Roberts B, Armstrong W, Miller MA, Hultner ML, Castillo AP, Ducom J-C, Topol EJ, Steinhubl SR (2016) Privacy and security in the era of digital health: what should translational researchers know and do about it? Am J Trans Res 8(3):1560–1580
Hoffman S, Podgurski A (2013) Big bad data: law, public health, and biomedical databases. J Law Med Ethics 41:56–60
Thorpe JH, Gray EA (2015) Law and the Public’s Health. Big data and public health: navigating privacy laws to maximize potential. Public Health Rep 130(2):171–175
Ward JC (2014) Oncology reimbursement in the era of personalized medicine and big data. J Oncol Pract 10(2):83–86
Booch G (2014) The human and ethical aspects of big data. IEEE Softw 31(1):20–22
Leszczynski A (2015) Spatial big data and anxieties of control. Environ Plan D Soc Space 33(6):965–984
Rothstein MA (2015) Ethical issues in big data health research: currents in contemporary bioethics. J Law Med Ethics 43(2):425–429
Shull F (2014) The true cost of mobility? IEEE Softw 31:5–9
Solove DJ (2013) Introduction: privacy self-management and the consent dilemma. Harvard Law Rev 126(7):1880–1903
Vaidhyanathan S, Bulock C (2014) Knowledge and dignity in the era of big data. Ser Librarian 66(1–4):49–64
Wang H, Jiang X, Kambourakis G (2015) Special issue on security, privacy and trust in network-based big data. Inf Sci 318:48–50
Jovanovi U, Stimec A, Vladusi D (2015) Big-data analytics: a critical review and some future directions. Int J Bus Intel Data Mining 10(4):337–355
Cohen J, Cohen P, West SG, Aiken LS (2003) Applied multiple regression/correlation analysis for the behavioral sciences, 3rd edn. Lawrence Erlbaum Associates, Mahwah
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Strang, K.D., Sun, Z. Big Data Paradigm: What is the Status of Privacy and Security?. Ann. Data. Sci. 4, 1–17 (2017). https://doi.org/10.1007/s40745-016-0096-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40745-016-0096-6