Towards assessing the quality evolution of Open Data portals

As of today, the Open Data movement enjoys great popularity among governments and public institutions and also increasingly in industry by promising transparency for the citizens, more efficient and effective public sectors or the chance to outsource innovative use of the published data. However, first critical voices appear addressing the emerging issue of low quality in the meta data and data source which is serious risk that could throw off the open data project.1 However, to the best of our knowledge there exists no comprehensive quantitative and objective reports about the actual quality of Open Data. Various efforts already exist to study different aspects of Open Data portals which are the main platforms to publish and find datasets. For instance, the Open Data Barometer project assesses the readiness of countries to exploit their Open Data efforts and the achieved impact based on expert judgements.2 Similarly, the Open Data Census provides a survey for data portal owners to analyse their data in more detail.3 The PoDQA project (Calero, Caro, & Piattini, 2008) addresses the evaluation of the quality of a Web Portal by defining a data quality model containing 42 characteristics. While some aspects of Open Data quality align with the ones of Web Portals, we identified domain-specific quality dimension in the context of Open Data (e.g., the openness of provided data based on the license or format ). More related to a data quality assessment is the OPQUAST project4 which provides a check-list for Open Data publishing, including some quality aspects. We can conclude and also identified by Reiche, Höfig, and Schieferdecker (2014), that there is a need for an automatic quality assessment and monitoring framework to better understand quality issues in Open Data portals and study the impact of improvement methods over time. In this work, we present our effort for such a framework, critically discuss our intrinsic and contextual quality metrics and report on early findings which provide insights for future directions.