As data volume explodes, nurse scientists grapple with ways to adapt to the big data movement without jeopardizing its epistemic values and theoretical focus that celebrate while acknowledging the authority and unity of its body of knowledge. In this article, the authors describe big data and emphasize ways that nursing science brings value to its study. Collective nursing voices that call for more nursing engagement in the big data era are answered with ways to adapt and integrate theoretical and domain expertise from nursing into data science.
BairdD. (2004). Thing knowledge: A philosophy of scientific instruments. Berkeley: University of California Press.
2.
BakkenS.ReameN. (2016). The promise and potential perils of big data for advancing symptom management research in populations at risk for health disparities. Annual Review of Nursing Research, 34(1), 247-260.
3.
BrennanP.BakkenP. (2015). Nursing needs big data and big data needs nursing. Journal of Nursing Scholarship, 47(5), 477-484.
4.
ClancyT. R.BowlesK. H.GelinasL.AndrowichI.DelaneyC.MatneyS.SensmeierJ.WarrenJ.WeltonJ.WestraB. (2014). A call to action: Engage in big data science. Nursing Outlook, 62, 64-65.
5.
DeVonH. A.RiceM.PicklerR.Krause-ParelloC. A.RichmondT. S. (2016). Setting nursing science priorities to meet contemporary health care needs. Nursing Outlook, 64(4), 399-401.
6.
EndersT.MorinA.PawlakB.GreyM.RubensteinA. (2016). Advancing healthcare transformation: A new era for academic nursing. Retrieved August29, 2017 from http://www.aacn.nche.edu/AACN-Manatt-Report.pdf
7.
GennaroS. (2016). Evolving methodologies and technologies in nursing science. Journal of Nursing Scholarship, 48(3), 221-222.
8.
GephartS. M.BristolA. A.DyeJ. L.FinleyB. A.CarringtonJ. M. (2016). Validity and reliability of a new measure of nursing experience with unintended consequences of electronic health records. Computer Informatics Nursing, 34(10), 436-447.