Adding time to the relational model has been a daunting task [1, 2, 3, 4]. More than two dozen time-extended relational data models have been proposed over the last fifteen years . Most of these are valid-time models. Each fact in a validtime relation has associated the time when it is true in the modeled reality. Other models support transaction-time relations where each fact has associated the time when it is current in the database. A few support both valid and transaction time [6, 7, 8, 9, 10]; such models are termed bitemporal. As a whole, these data models are referred to as temporal data models . This chapter introduces the data model upon which TSQL2 is based. A data model can be said to consist of a query language, objects manipulated by the query language, an update language for updating the objects, and a mechanism for specifying integrity constraints. In this chapter we focus on the objects, temporal relations. Subsequent chapters will address historical selection and projection, aggregates, and the other aspects necessary to define a comprehensive extension to SQL incorporating time. While existing data models differ on many dimensions, perhaps the most frequently stated distinction is between tuple timestamping and first normal form (1NF), on one hand, and attribute-value timestamping and non-1NF, on the other. Each of the two approaches has associated difficulties. Remaining within 1NF (an example being the timestamping of tuples with valid and transaction start and end times ) may introduce redundancy because attribute values that change at different times are repeated in multiple tuples. The non-1NF models, one being timestamping attribute values with sets of intervals , may not be capable of directly using existing relational storage structures or query evaluation techniques that depend on atomic attribute values.