A bottom-up, knowledge-aware approach to integrating and querying web data services
As a wealth of data services is becoming available on the Web, building and querying Web applications that effectively integrate their content is increasingly important. However, schema integration and ontology matching with the aim of registering data services often requires a knowledge-intensive, tedious, and error-prone manual process.
 We tackle this issue by presenting a bottom-up, semi-automatic service registration process that refers to an external knowledge base and uses simple text processing techniques in order to minimize and possibly avoid the contribution of domain experts in the annotation of data services. The first by-product of this process is a representation of the domain of data services as an entity-relationship diagram, whose entities are named after concepts of the external knowledge base matching service terminology rather than being manually created to accommodate an application-specific ontology. Second, a three-layer annotation of service semantics (service interfaces, access patterns, service marts) describing how services “play” with such domain elements is also automatically constructed at registration time. When evaluated against heterogeneous existing data services and with a synthetic service dataset constructed using Google Fusion Tables, the approach yields good results in terms of data representation accuracy.
 We subsequently demonstrate that natural language processing methods can be used to decompose and match simple queries to the data services represented in three layers according to the preceding methodology with satisfactory results. We show how semantic annotations are used at query time to convert the user's request into an executable logical query. Globally, our findings show that the proposed registration method is effective in creating a uniform semantic representation of data services, suitable for building Web applications and answering search queries.