Automated Quality Assessment of Metadata Across Open Data Portals

Publication: Scientific journalJournal articlepeer-review


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 a 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.
Original languageEnglish
JournalJournal of Data and Information Quality
Issue number1
Publication statusPublished - 2016

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102
  • 102001 Artificial intelligence
  • 502050 Business informatics
  • 102015 Information systems

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