Abstract
Commercial reuse of open government data in value added services has gained a lot of interest both as practice and as a research topic over the last few years. However, utilizing open data without proper understanding of potential quality issues carries the risk of undermining the value of the service that relies on public sector information. Instead of establishing a data quality assessment framework this research considers a review of typical open data quality issues and intends to connect them to the causes leading to these various data problems. Open data specific problems are concluded from a case study and then theoretical and empirical arguments are used to connect them to root causes emerging from the peculiarities of the public sector data management process. This way both practitioners could be more conscious about appropriate cleansing methods and participants shaping the data management process could aim at eliminating root causes of data quality issues.
Highlights
While the idea of open government data (OGD) has been around for some time, every few years there is a rejuvenated scientific interest in the topic
Under the above objective the following research questions are proposed: 1) What is the status of the quality of Open Government Data from the point of view of ‘content’? 2) What are the main reasons behind OD content issues in public context? 3) What to do about improving content quality of OGD? This paper focuses on the second question, using the first as support – but would not have the room to address the last question here
This research paper has argued that while current OD quality frameworks are strong tools when it comes to assessing OD quality or measuring maturity of data released, they are inadequate when it comes to helping public organizations how to release their data in better shape and how to improve quality as experienced by the end user during reuse
Summary
While the idea of open government data (OGD) has been around for some time, every few years there is a rejuvenated scientific interest in the topic. One of the main conditions of successful reuse is quality data [6] It is no surprise, that over the years a lot of scientific and on-the-field efforts have been reported to address the issue. The assumption here is that guidelines related to various aspects of quality are no help mainly because they do not focus (enough) on the root causes of ODG quality issues. While there is considerable research efforts addressing certain specific areas related to producing good quality open data, relatively less attention is paid to why data quality issues are still present despite the best efforts and available experience
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