Authors:
Thomas Hornung
;
Kai Simon
and
Georg Lausen
Affiliation:
Institut für Informatik, Universität Freiburg, Germany
Keyword(s):
Assisted Mashup Generation, Deep Web, Information Integration.
Related
Ontology
Subjects/Areas/Topics:
Accessibility Issues and Technology
;
Data Engineering
;
Databases and Datawarehouses
;
Internet Technology
;
Metadata and Metamodeling
;
Multimedia and User Interfaces
;
Ontologies and the Semantic Web
;
Ontology and the Semantic Web
;
Searching and Browsing
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Personalization
;
Web Services and Web Engineering
;
XML and Data Management
Abstract:
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 machine-processable 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 parallel.