A query answering system for data with evolution relationships

Evolving data has attracted considerable research attention. Researchers have focused on modeling and querying of schema/instance-level structural changes, such as, insertion, dele-tion and modification of attributes. Databases with such a func-tionality are known as temporal databases. A limitation of the tem-poral databases is that they treat changes as independent events, while often the appearance (or elimination) of some structure in the database is the result of an evolution of some existing struc-ture. We claim that maintaining the causal relationship between the two structures is of major importance since it allows additional reasoning to be performed and answers to be generated for queries that previously had no answers. We present the TrenDS, a system for exploiting the evolution relationships between the structures in the database. In particular, our system combines different struc-tures that are associated through evolution relationships into virtual structures to be used during query answering. The virtual struc-tures define “possible ” database instances, in a fashion similar to the possible worlds in the probabilistic databases. TrenDS uses a query answering mechanism that allows queries to be answered over these possible databases without materializing them. Eval-uation of such queries raises many technical challenges, since it requires the discovery of Steiner forests on the evolution graphs