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Data Publishing through the Cloud: A Data- and Platform-as-a-Service Approach for Efficient Data Publication and Consumption (DaPaaS)
Start date: Nov 1, 2013, End date: Oct 31, 2015 PROJECT  FINISHED 

While in recent years a large number of datasets has been published as open (and often linked) data, applications utilizing these open and distributed data have been rather few. Reasons include, amongst others, the technical complexity and cost of publishing and providing access to the data, lack of monetization incentives on the provider side, and lack of simplified and unified solutions for data consumption in a multi-platform way. The DaPaaS project directly addresses these challenges by developing a software infrastructure combining Data-as-a-Service (DaaS) and Platform-as-a-Service (PaaS) for open data, with the aim of optimizing publication of Open Data and development of data applications. Addressing the data consumption aspect by developing novel cross-platform interfaces to data applications, DaPaaS extensively covers the life cycle of cost-efficient data publishing and consumption. Backed by the development of a methodology for data use in the DaPaaS infrastructure, the project will deliver an intuitive platform that simplifies data publication, as well as cross-platform data consumption, thus enabling a sustainable infrastructure for efficient and simplified reuse of open data. Core innovations include: an open DaaS and PaaS, unified Linked Data access, integrated DaaS and PaaS for open data, lowering the complexity of open data publishing and consumption for non-experts.Sustainable exploitation of the project results is ensured through a strong participation of SMEs in the consortium. The participating SMEs are among the world's leading organizations in the field of Open Data, with strong knowledge transfer experience and unique technologies in Linked Data, Semantic Web, data integration and mobile development, with strong links across both public and private sectors, and are committed to a joint development of unique technologies for effectively and efficiently supporting the life cycle of reuse of open data.
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