We are concerned with temporalreasoning problems where there is uncertainty about the order in which events occur. The task of temporal reasoning is to derive an event sequence consistent with a given set of ordering constraints immediately following which one or more conditions have speci ed statuses. Previous research shows that the associated decision problems are hard even for very restricted cases. In this paper, we present a framework of localized temporal reasoning which use subd abstraction to exploit structure in temporal ordering and causal interaction. We investigate (1) locality regarding ordering constraints that group events hierarchically into sets called regions, and (2) locality regarding causal interactions among regions, which is characterized by subsets of the set of conditions. The complexity for an instance of temporal reasoning is quanti ed by the sizes of the characteristic subsets of conditions and the numbers of child regions of individual regions in the regi...