Human factors/ergonomics implications of big data analytics: Chartered Institute of Ergonomics and Human Factors annual lecture

Abstract

In recent years, advances in sensor technology, connectedness and computational power have come together to produce huge data-sets. The treatment and analysis of these data-sets is known as big data analytics (BDA), and the somewhat related term data mining. Fields allied to human factors/ergonomics (HFE), e.g. statistics, have developed computational methods to derive meaningful, actionable conclusions from these data bases. This paper examines BDA, often characterised by volume, velocity and variety, giving examples of successful BDA use. This examination provides context by considering examples of using BDA on human data, using BDA in HFE studies, and studies of how people perform BDA. Significant issues for HFE are the reliance of BDA on correlation rather than hypotheses and theory, the ethics of BDA and the use of HFE in data visualisation.

Abstract

Practitioner Summary: Human factors/ergonomics practitioners are increasingly likely to work with the large data bases and novel software associated with big data analytics (BDA) and similar fields such as data mining. This paper shows the characteristics of BDA and details methodological and ethical issues that arise in BDA.

Keywords::

• big data
• data mining
• correlation
• ethics

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Funding

No funding was received for the work reported in this paper.