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Enhancing the Quality of Open Data

  • Kieron O’Hara
Chapter
Part of the Synthese Library book series (SYLI, volume 358)

Abstract

This paper looks at some of the quality issues relating to open data. This is problematic because of an open-data specific paradox: most metrics of quality are user-relative, but open data are aimed at no specific user and are simply available online under an open licence, so there is no user to be relevant to. Nevertheless, it is argued that opening data to scrutiny can improve quality by building feedback into the data production process, although much depends on the context of publication. The paper discusses various heuristics for addressing quality, and also looks at institutional approaches. Furthermore, if the open data can be published in linkable or bookmarkable form using Semantic Web technologies, that will provide further mechanisms to improve quality.

Keywords

Open Data Primary User Data Provider Open Licence Open Government Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work is supported by SOCIAM: The Theory and Practice of Social Machines, funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/J017728/1. Thanks are owing to audiences at a number of talks and conferences, including the Information Quality Symposium at the AISB/IACAP World Congress 2012, Birmingham, July 2012.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Electronics and Computer ScienceUniversity of SouthamptonSouthamptonUK

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