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Data quality and the Internet of Things

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Abstract

The Internet of Things (IoT) is driving technological change and the development of new products and services that rely heavily on the quality of the data collected by IoT devices. There is a large body of research on data quality management and improvement in IoT, however, to date a systematic review of data quality measurement in IoT is not available. This paper presents a systematic literature review (SLR) about data quality in IoT from the emergence of the term IoT in 1999 to 2018. We reviewed and analyzed 45 empirical studies to identify research themes on data quality in IoT. Based on this analysis we have established the links between data quality dimensions, manifestations of data quality problems, and methods utilized to measure data quality. The findings of this SLR suggest new research areas for further investigation and identify implications for practitioners in defining and measuring data quality in IoT.

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Authors and Affiliations

  1. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway 15, Ultimo, NSW, 2007, Australia

    Caihua Liu & Didar Zowghi

  2. Faculty of Computer Science, University of Koblenz-Landau, Universitätsstraße 1, 56070, Koblenz, Germany

    Patrick Nitschke & Susan P. Williams

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  1. Caihua Liu
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  2. Patrick Nitschke
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  4. Didar Zowghi
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Correspondence to Caihua Liu.

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Appendix

Appendix

List of articles included in the SLR:

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  11. S11

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  14. S14

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  30. S30

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  31. S31

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  34. S34

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  35. S35

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  36. S36

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  37. S37

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  38. S38

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  39. S39

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  40. S40

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  41. S41

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  42. S42

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  43. S43

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  44. S44

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  45. S45

    Ukil A, Bandyopadhyay S, Pal A (2015) IoT data compression: Sensor-agnostic approach. In: Proc 2015 Data Compression Conf, pp 303–312

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Liu, C., Nitschke, P., Williams, S.P. et al. Data quality and the Internet of Things. Computing 102, 573–599 (2020). https://doi.org/10.1007/s00607-019-00746-z

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