Automated Quality Assessment of Metadata across Open Data Portals
Abstract: The Open Data movement has become a driver for publicly available data on the Web. More and more data – from governments, public institutions but also from the private sector – is made available online and is mainly published in so called Open Data portals. However, with the increasing number of published resources, there are a number of concerns with regards to the quality of the data sources and the corresponding metadata, which compromise the searchability, discoverability and usability of resources.
In order to get a more complete picture of the severity of these issues, the present work aims at developing a generic metadata quality assessment framework for various Open Data portals: we treat data portals independently from the portal software frameworks by mapping the specific metadata of three widely used portal software frameworks (CKAN, Socrata, OpenDataSoft) to the standardized DCAT metadata schema. We subsequently define several quality metrics, which can be evaluated automatically and in an efficient manner. Finally, we report findings based on monitoring a set of over 260 Open Data portals with 1.1M datasets. This includes the discussion of general quality issues, e.g. the retrievability of data, and the analysis of our specific quality metrics.
Authors: Sebastian Neumaier, Jürgen Umbrich, and Axel Polleres, Vienna University of Economics and Business, Vienna, Austria
Journal: The paper will be published in the Journal of Data and Information Quality (JDIQ).