Enhancing the Quality of Open Data

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.