With the emergence of the open data movement, hundreds of thousands of datasets from various concerns are now freely available on the Internet. The access to a good number of these datasets is carried out through Web services which provide a standard way to interact with data. In this context, user's queries often require the composition of multiple data Web services to be answered. Defining the semantics of data services is the first step towards automating their composition. An interesting approach to define the semantics of data services is by describing them as semantic views over a domain ontology. However, defining such semantic views cannot always be done with certainty, especially when the service's outputs are too complex. In this paper, we propose a probabilistic approach to model the semantics uncertainty of data services. In our approach, a data service with an uncertain semantics is described by several possible semantic views, each one is associated with a probability. Services along with their possible semantic views are represented in a Block-Independent-Disjoint (noted BID) probabilistic service registry, and interpreted based on the Possible Worlds Semantics. Based on our modeling, we study the problem of interpreting an existing composition involving services with uncertain semantics. We also study the problem of compositing uncertain data services to answer a user query, and propose an efficient method to compute the different possible compositions and their probabilities.

In this demo paper, we present a new privacy preserving composition execution system. Our system allows to execute queries over multiple data services without revealing any extra information to any of the involved services. None of involved services (and their providers) is able to infer any information about the data the other services provide beyond what is permitted

In this paper, we propose a new approach to automatically compose data providing Web services. Our approach exploits existing mature works done in data integration systems. Specifically, data providing services are modeled as RDF Parameterized views over mediated ontologies. Then, an RDF oriented algorithm to compose services based on query rewriting techniques was devised. We apply also an optimization algorithm on the generated composition to speed up its execution. The results of our experiments show that the algorithms scale up very well up to a large number of services, covering thus most realistic applications.