Applications of scientific workflows are going to be more widespread and important to our living and lives. The intrinsic characteristics of scientific workflows are data- and computing-intensive, heterogeneous data representation and distributed execution environments. Scientists use different equipment to retrieve source data by monitoring objects and then store or process on many different workstations. Actor Petri net Model (APnM) helps develop scientific work-flows effectively and efficiently within collaboration and cooperation work mode. Scientific workflow environments based on APnM can help scientists pay close attention to functional components development, and choose flexible mechanisms on error management, transaction and exception management, and priority processing. Scientific workflows represented based on APnM can be operated both on design and run time to support trial and error development. From the perspective of software engineering, it is a suitable level of indirection to resolve the development, testing, and simulation complexity of scientific workflows.