Suchergebnisse

Solving existing policy making problems such as the lack of transparency and the inability to crosscheck and assess the actual impact of implemented policies, as well as improving the empirical foundation for more factual, objective, evidence-based deliberation of governmental policies is amongst the top priorities in modern citizens' agendas. The proposed approach aims at making better use of Europe's open public data resources and empowering citizens - especially the younger generation - and policy makers to better assess government policies in the policy analysis and monitoring phases of the policy cycle. In this respect, it specifies the methodological framework and conceptual architecture of an easy to use platform, allowing citizens and public officials to create, apply, share, embed, annotate and discuss causal models, charts and graphs of historical data from open data sources.

During the past years, various activities and concepts have shaped and prepared the path for the development of urban environments toward smart cities across the world. One of the initial activities was relating to the opening of vast amounts of data from various public administrations and utility companies within a city in order to create a viable eco-system of urban services and applications. Thereby, the harvested metadata needed to be verified in terms of correctness and a corresponding level of quality had to be assured. In addition, the concept of an Open Urban Platform emerged as an overall solution for smart cities Information Communication Technology (ICT) in the sense that an abstract reference model was established and standardized, providing an overall picture of the ICT structures within a city. Within this article, we use the Open Urban Platform concept as the basics to describe and map our activities within the Open Data domain, focusing mainly on the Open Data prototype for German Open Governmental Data—namely GovData.DE. Thereby, we describe our metadata harvesting and metadata quality assurance approach and discuss on lessons learned, which flow into the definition of metadata quality metrics and have the potential to lead to a corresponding standard within the Deutsches Institut für Normung e.V. (DIN) German national standardization.