Schema and data: A holistic approach to mapping, resolution and fusion in information integration

Abstract. To integrate information, data in different formats, from different, potentially overlapping sources, must be related and transformed to meet the users' needs. Ten years ago, Clio introduced nonprocedural schema mappings to describe the relationship between data in heterogeneous schemas. This enabled powerful tools for mapping discovery and integration code generation, greatly simplifying the integration process. However, further progress is needed. We see an opportunity to raise the level of abstraction further, to encompass both data-and schema-centric integration tasks and to isolate applications from the details of how the integration is accomplished. Holistic information integration supports iteration across the various integration tasks, leveraging information about both schema and data to improve the integrated result. Integration independence allows applications to be independent of how, when, and where information integration takes place, making materialization and the timing of transformations an optimization decision that is transparent to applications. In this paper, we define these two important goals, and propose leveraging data mappings to create a framework that supports both data-and schema-level integration tasks