Emerging Technologies for Data Research: Implications for Bias, Curation, and Reproducible Results

Abstract

Information overload is a norm in the era of big data. The threats and opportunities presented to organizations, institutions, and individuals have only increased in their volume and velocity. This chapter looks at how an individual’s scanning of environmental and external information is affected by bias. The term subscriber or subscription bias is introduced. Tools for increasing the speed of processing large new data relationships through visualization are evaluated. Additionally, the role and benefit of Cognitive Analytics in presenting fresh insight, as well as its role in mitigating publication and other biases, is reviewed. Last, some of the networked world tools and web services available to researchers and practitioners are considered in terms of how these emerging offerings can enhance productivity and their human capital with reusability of data and reproducibility of results.

Citation

Worden, D.J. (2017), "Emerging Technologies for Data Research: Implications for Bias, Curation, and Reproducible Results", Russ, M. (Ed.) Human Capital and Assets in the Networked World, Emerald Publishing Limited, Leeds, pp. 61-83. https://doi.org/10.1108/978-1-78714-827-720171003