ABSTRACT

Data Warehouse systems aim at integrating data from multiple heterogeneous, distributed, autonomous data sources. Due to changing business needs the data warehouse systems are never meant to be static. Changes in the data source structure or business requirements would result in the evolution of data warehouse schema structure. When data warehouse schema evolves the dependent modules such as its mappings, queries and views gets affected. The existing works on data warehouse evolution focus only on schema evolution at the physical level. As ontology seems to be a promising solution in data warehouse research, the proposed framework handles data warehouse schema evolution at ontological level. Moreover, it analyses the impact of the dependent modules and proposes methods to automatically adapt to changes.