A common method for storing knowledge in databases is in the form of attribute values. For databases with spatial and temporal knowledge however, it is not feasible to store all of the attribute values that one might be interested in. For example, in the spatial domain for a geographic database it is impossible to anticipate the very large number of queries regarding nearness, spatial adjacency, or the possibility of finding feasible paths between arbitrary locations. Similarly in the temporal domain it is impossible to anticipate all queries regarding the temporal duration, range, and overlap of complex temporal events. We have developed both spatial and temporal representations for databases to handle the inferring of attribute values as a result of possible queries. The temporal representation involves the creation of time tags for attribute values and information regarding the persistence of those values. The spatial representation consists of a labeled array in which each label corresponds to to a unique object (or class of objects) in the database. Preprocessing of spatial “scenes” allows the system to rapidly obtain paths, determine objects in a given region of interest, etc. These representations, and their application to typical geographic/temporal databases are described in the paper. A natural language interface, developed earlier, was extended to work with these spatial and temporal representations.