Current specialized planners for query processing are designed to work in local, reliable, and predictable environments. However, there are a number of problems that arise in gathering information from large networks of distributed information. In this environment actions can be executed in parallel to exploit distributed resources, new goals come into the system in the midst of execution, actions may fail due to exogenous events and need to be replanned, and there is incomplete information about the world. We have developed a planner called Sage that addresses the issues that arise in this environment. This system integrates previous work on planning, execution, replanning, and sensing and extends this work to support simultaneous and interleaved planning and execution. Sage has been applied to the problem of information gathering to provide a flexible and efficient system for integrating heterogeneous and distributed data and has been used in the domains of logistics planning and trauma care.