text: 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.
  @cite_14: In this paper we suggest that the full scientific potential of workflows will be achieved through mechanisms for sharing and collaboration, empowering scientists to spread their experimental protocols and to benefit from those of others. To facilitate this process we have designed and built the Experimentmy Virtual Research Environment for collaboration and sharing of workflows and experiments. In contrast to systems which simply make workflows available, Experimentmy provides mechanisms to support the sharing of workflows within and across multiple communities. It achieves this by adopting a social web approach which is tailored to the particular needs of the scientist. We present the motivation, design and realisation of Experimentmy.
  @cite_13: 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.
summary: 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 .