State-of-the-art scientific instruments and simulations routinely produce massive datasets requiring intensive processing to disclose key features of the artifact or model under study. Scientists commonly call these data-processing pipelines, which are structured according to the pipe and-filter architecture pattern.1 Different stages typically communicate using files; each stage is an executable program that performs the processing needed at that point in the pipeline.The MeDICi (Middleware for Data-Intensive Computing) Integration Framework supports constructing complex software pipelines from distributed heterogeneous components and controlling qualities of service to meet performance, reliability and communication requirements.