Abstract: Galaxy is a scientific workflow, data integration, and data and analysis persistence and publishing platform that aims to make computational biology accessible to research scientists that do not have computer programming experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system. While user-friendly and intuitive for doing small to medium-scale computations, it currently has limited support for large-scale parallel and distributed computing. The Swift parallel scripting framework is capable of composing ordinary applications into parallel scripts that can be run on multiscale distributed and performance computing platforms. Swift is an implicitly parallel programming language that allows the writing of scripts that distribute program execution across distributed computing resources, including clusters, clouds, grids, and super computers. Swift implementations are open source under the Apache License, version 2.0.In complex distributed environments, and often the user end of the application lifecycle slows because of the technical complexities brought in by the scale, access methods, and resource management nuances. Galaxy offers a simple way of designing, composing, executing, reusing, and reproducing application runs. Integration between the Swift and Galaxy systems can accelerate science as well as bring the respective user communities together in an interactive, user friendly, parallel and distributed data analysis environment enabled on a broad range of computational infrastructures.
Keywords: Swift, Galaxy, Big Data, scientific applications.