Ontology type: schema:ScholarlyArticle
2017-03
AUTHORSKenneth David Strang, Zhaohao Sun
ABSTRACTWe 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% (r2=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. More... »
PAGES1-17
http://scigraph.springernature.com/pub.10.1007/s40745-016-0096-6
DOIhttp://dx.doi.org/10.1007/s40745-016-0096-6
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