Temporal Semistructured Data Models and Data Warehouses

This chapter describes a graph-based approach to represent information stored in a data warehouse, by means of a temporal semistructured data model. We consider issues related to the representation of semistructured data warehouses, and discuss the set of constraints needed to manage in a correct way the warehouse time, that is the time dimension considered storing data in the data warehouse itself. We use a temporal semistructured data model because a data warehouse can contain data coming from different and heterogeneous data sources. This means that data stored in a data warehouse are semistructured in nature; that is, in different documents the same information can be represented in different ways, and the document schemata can be available or not. Moreover, information stored in a data warehouse is often time varying, thus as for semistructured data, also in the data warehouse context, it could be useful to consider time.