The Grid and Cloud User Support Environment (gUSE) enables users convenient and easy access to grid and cloud infrastructures by providing a general purpose, workflow-oriented graphical user interface to create and run workflows on various Distributed Computing Infrastructures (DCIs). Its arrangements for creating and modifying existing workflows are, however, non-intuitive and cumbersome due to the technologies and architecture employed by gUSE. In this paper, we outline the first integrated web-based workflow editor for gUSE with the aim of improving the user experience for those with industrial data workflows and the wider gUSE community. We report initial assessments of the editor's utility based on users' feedback. We argue that combining access to diverse scalable resources with improved workflow creation tools is important for all big data applications and research infrastructures.
While Galaxy is widely used, especially by the biomedical community, the data management capabilities are quite restricted for large data and necessitate data transfers between single jobs of a workflow to the server hosting the back-end of Galaxy. However, Galaxy can map to the highly parallelized enactments of Swift @cite_13 . Another workflow system well established in the biomedical community is Taverna but the workflow canvas is only available as a workbench. The workflows can be shared via the social website myExperiment @cite_14 .
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The Galaxy science portal is a popular gateway to data analysis and computational tools for a broad range of life sciences communities. While Galaxy enables users to overcome the complexities of integrating diverse tools into unified workflows, it has only limited capabilities to execute those tools on the parallel and often distributed high-performance resources that the life sciences fields increasingly requires. We outline here an approach to meet this pressing requirement with the Swift parallel scripting language and its distributed runtime system. Swift's model of computation - implicitly parallel functional dataflow - is an elemental abstraction to which the core computing model of Galaxy maps very closely. We describe an integration between Galaxy and Swift that is transforming Galaxy into a much more powerful science gateway, retaining its user-friendly nature while extending its power to execute highly scalable workflows on diverse parallel environments. Accessing and analyzing the exponentially expanding genomic sequence and functional data pose a challenge for biomedical researchers. Here we describe an interactive system, Galaxy, that combines the power of existing genome annotation databases with a simple Web portal to enable users to search remote resources, combine data from independent queries, and visualize the results. The heart of Galaxy is a flexible history system that stores the queries from each user; performs operations such as intersections, unions, and subtractions; and links to other computational tools. Galaxy can be accessed at http: g2.bx.psu.edu. Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http: usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis. As next-generation sequencing becomes an indispensible tool for biomedical research, it is crucial to provide analysis solutions that are usable and cost effective for biomedical researchers. Galaxy Cloud addresses this by combining the accessible Galaxy interface with automated management of cloud computing resources. Unlike purpose-built solutions, Galaxy allows users either to use existing tested best practices in the form of workflows or to construct their own analyses for novel tasks. Galaxy Cloud instances are owned and controlled entirely by the user who created them and can be used effectively in secure private clouds. Thus, Galaxy Cloud provides a solution that retains user control and privacy, makes complex analysis accessible and enables the use of practically limitless on-demand computing resources.