  Data exchange is the problem of transforming data that is structured under a
source schema into data structured under another schema, called the target
schema, so that both the source and target data satisfy the relationship
between the schemas. Even though the formal framework of data exchange for
relational database systems is well-established, it does not immediately carry
over to the settings of temporal data, which necessitates reasoning over
unbounded periods of time. In this work, we study data exchange for temporal
data. We first motivate the need for two views of temporal data: the concrete
view, which depicts how temporal data is compactly represented and on which the
implementations are based, and the abstract view, which defines the semantics
of temporal data as a sequence of snapshots. We first extend the chase
procedure for the abstract view to have a conceptual basis for the data
exchange for temporal databases. Considering non-temporal source-to-target
tuple generating dependencies and equality generating dependencies, the chase
algorithm can be applied on each snapshot independently. Then we define a chase
procedure (called c-chase) on concrete instances and show the result of c-chase
on a concrete instance is semantically aligned with the result of chase on the
corresponding abstract instance. In order to interpret intervals as constants
while checking if a dependency or a query is satisfied by a concrete database,
we will normalize the instance with respect to the dependency or the query. To
obtain the semantic alignment, the nulls in the concrete view are annotated
with temporal information. Furthermore, we show that the result of the concrete
chase provides a foundation for query answering. We define naive evaluation on
the result of the c-chase and show it produces certain answers.
