using schematically heterogeneous structures
Schematic heterogeneity arises when information that is represented as data under one schema, is represented within the schema (as metadata) in another. Schematic heterogeneity is an important class of heterogeneity that arises frequently in integrating legacy data in federated or data warehousing applications. Traditional query languages and view mechanisms are insufficient for reconciling and translating data between schematically heterogeneous schemas. Higher order query languages, that permit quantification over schema labels, have been proposed to permit querying and restructuring of data between schematically disparate schemas. We extend this work by considering how these languages can be used in practice. Specifically, we consider a restricted class of higher order views and show the power of these views in integrating legacy structures. Our results provide insights into the properties of restructuring transformations required to resolve schematic discrepancies. In addition, we show how the use of these views permits schema browsing and new forms of data independence that are important for global information systems. Furthermore, these views provide a framework for integrating semi-structured and unstructured queries, such as keyword searches, into a structured querying environment. We show how these views can be used with minimal extensions to existing query engines. We give conditions under which a higher order view is usable for answering a query and provide query translation algorithms.
use schema heterogeneity structure informal data metadata class federated data warehousing applications query languages queries queries language views translation order label practical power browse global information system environments minimal extensibility usability algorithm  framework  query