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arXiv · 1812.05804

Data Provenance for Sport

Andrew J. Simmons·Scott Barnett·Simon Vajda·Rajesh Vasa
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Abstract

Data analysts often discover irregularities in their underlying dataset, which need to be traced back to the original source and corrected. Standards for representing data provenance (i.e. the origins of the data), such as the W3C PROV standard, can assist with this process, however require a mapping between abstract provenance concepts and the domain of use in order to apply them effectively. We propose a custom notation for expressing provenance of information in the sport performance analysis domain, and map our notation to concepts in the W3C PROV standard where possible. We evaluate the functionality of W3C PROV (without specialisations) and the VisTrails workflow manager (without extensions), and find that as is, neither are able to fully capture sport performance analysis workflows, notably due to limitations surrounding capture of automated and manual activities respectively. Furthermore, their notations suffer from ineffective use of visual design space, and present potential usability issues as their terminology is unlikely to match that of sport practitioners. Our findings suggest that one-size-fits-all provenance and workflow systems are a poor fit in practice, and that their notation and functionality need to be optimised for the domain of use.

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Andrew J. Simmons, Scott Barnett, Simon Vajda, Rajesh Vasa. 2018-12-14. Data Provenance for Sport. https://arxiv.org/abs/1812.05804

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