In this paper, we tackle privacy issues of data sharing services in a cloud environment. We propose a service- oriented privacy-preserving model for data integration across autonomous clouds. Our model allows to execute aggregations of cloud data sharing services without revealing any extra information to any of the involved services. Thus, involved services enforce locally their privacy policies by applying their own access control models and data anonymization algorithms. We illustrate lack of data protection in current data sources through examples of querying data in a healthcare system.

We propose a service-oriented privacy-preserving model for data integration across autonomous clouds. Our model allows to execute aggregations of cloud data sharing services without revealing any extra information to any of the involved services, i.e., none of involved services nor their providers are able to learn/infer any information about the data the other services provide beyond what these services already know.

On-demand data integration is among the key challenges in Cloud Computing. In this paper, we present an ontology-based framework for describing and integrating data on the fly to answer transient business needs. We provide a semantic modeling for cloud's data services. The proposed modeling makes it possible to automatically resolve the different types of data heterogeneity that would arise when data from heterogeneous and autonomous providers need to be combined together to answer the business's data needs.

In a collaborative design environment, various software tools are utilized to enhance the product development. This entails a meaningful representation and exchange of product data semantics across these different systems. Semantic interoperability of product information refers to enabling the exchange of design intelligence, including construction history, parameters, features, and constraints. This is a crucial difference compared to current standards such as STEP that deliver "dumb" geometry, where no design intent is associated. To enable semantics data exchange, we propose an ontology-based approach, consisting in developing a "Common Design Features Ontology", called CDFO. Interoperability among ontologies is fulfilled by defining several mapping rules. We use a descriptive logic-based language, notably OWL DL to represent formally our ontology.