Mashing Up the DEEP Web - Research in Progress

Deep Web (DW) sources offer a wealth of structured, high-quality data, which is hidden behind human-centric user interfaces. Mashups, the combination of data from different Web services with formally defined query interfaces (QIs), are very popular today. If it would be possible to use DW sources as QIs, a whole new set of data services would be feasible. We present in this paper a framework that enables non-expert users to convert DW sources into machineprocessable QIs. In the next step these QIs can be used to build a mashup graph, where each vertex represents a QI and edges organize the data flow between the QIs. To reduce the modeling time and increase the likelihood of meaningful combinations, the user is assisted by a recommendation function during mashup modeling time. Finally, an execution strategy is proposed that queries the most likely value combinations for each QI in