An exploding demand for information services is pushing databases toward specialized and often incompatible approaches. Yet, the best solutions to the formidable technical challenges of each sub-field are often found in the convergence of techniques and models from different approaches. For instance, advanced active database systems support rule activation by complex temporal events, while complex patterns of temporal events have been the focus of languages for time-series analysis and temporal queries. Significant benefits are expected from the confluence of these areas of research. Moreover, the capability of reasoning with time is critical to model the dynamics of active databases, and to avoid undesirable rule behavior, such as non-termination. This project pursues a unified approach to the design and query optimization of languages for time-series analysis, temporal reasoning on databases, and active rules with composite events. In addition, the project is developing more effective temporal semantics for active database rules, and providing methods and tools to predict and control their behavior. This research will provide capabilities for a wide range of government and industrial applications that must reason with and manage temporal data.