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Time is essential in modeling the constantly changing world. However, conventional database systems represent the real world with only a tenseless snapshot that is inadequate for many applications where facts and data need to be interpreted in the context of time. In this work we examine some of the issues applicable to temporal modeling, including examples which illustrate the demands imposed by database management systems for global change research. The main contribution of this paper is the proposal of a framework for managing temporal information in scientific databases. The characteristics of this model are: (1) Time is treated as a basic data type and property. (2) Attribute stamping is adopted whereby the granularity of time can be identified by the user. (3) Time is treated explicitly in the query language. (4) A helical view of time is used for measuring the distance between two time points, and (5) the implications of temporal analysis are addressed.