Enabling On-Demand Mashups of Open Data with Semantic Services

Analogous to software-as-a-service (SaaS), platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS), data-as-a-service (DaaS) is used to provide data on demand to users over the Internet and is gaining popularity in the current cloud computing era. In particular, several Open Data initiatives have led to a number of data services in various formats becoming available online, and it remains a challenge to make full use of the data by transferring between and answering queries from different sources in a automatic, dynamic and meaningful manner. In this paper we propose a service-oriented, composition-based approach towards tackling the integration of open data services. We provide a formal, semantic-based modeling of data services and convert the integration problem into the service composition problem. Then the composition graph can be used to create the executable queries to the various data services. We illustrate our idea by using a case study in the real estate domain.