 Open data: Quality over quantityShazia Sadiq and Marta Indulska International Journal of Information Management, 2017, vol. 37, issue 3, 150-154 Abstract: Open data aims to unlock the innovation potential of businesses, governments, and entrepreneurs, yet it also harbours significant challenges for its effective use. While numerous innovation successes exist that are based on the open data paradigm, there is uncertainty over the data quality of such datasets. This data quality uncertainty is a threat to the value that can be generated from such data. Data quality has been studied extensively over many decades and many approaches to data quality management have been proposed. However, these approaches are typically based on datasets internal to organizations, with known metadata, and domain knowledge of the data semantics. Open data, on the other hand, are often unfamiliar to the user and may lack metadata. The aim of this research note is to outline the challenges in dealing with data quality of open datasets, and to set an agenda for future research to address this risk to deriving value from open data investments. Keywords: Open data; Data quality (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:37:y:2017:i:3:p:150-154 DOI: 10.1016/j.ijinfomgt.2017.01.003 Access Statistics for this article International Journal of Information Management is currently edited by Yogesh K. Dwivedi More articles in International Journal of Information Management from Elsevier |
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