Workflow

About: Workflow is a research topic. Over the lifetime, 31996 publications have been published within this topic receiving 498339 citations.

Transformation of componentized and extensible workflow to a declarative format

Abstract: Building a componentized workflow model. Each step of the workflow is modeled as an activity that has metadata to describe design time aspects, compile time aspects, and runtime aspects of the workflow step. A user selects and arranges the activities to create the workflow via user interfaces or application programming interfaces. The metadata associated with each of the activities in the workflow is collected to create a persistent representation of the workflow. Users extend the workflow model by authoring custom activities. The workflow may be compiled and executed.

Sliver : A BPEL workflow process execution engine for mobile devices

Abstract: The Business Process Execution Language (BPEL) has become the dominant means for expressing traditional business processes as workflows. The widespread deployment of mobile devices like PDAs and mobile phones has created a vast computational and communication resource for these workflows to exploit. However, BPEL so far has been deployed only on relatively heavyweight server platforms such as Apache Tomcat, leaving the potential created by these lower-end devices untapped. This paper presents Sliver, a BPEL workflow process execution engine that supports a wide variety of devices ranging from mobile phones to desktop PCs. We discuss the design decisions that allow Sliver to operate within the limited resources of a mobile phone or PDA. We also evaluate the performance of a prototype implementation of Sliver.

Genomics Virtual Laboratory: A Practical Bioinformatics Workbench for the Cloud.

Abstract: Background: Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets; workflow platform(s) enabling accessible, reproducible, portable analyses, through a flexible set of interfaces; highly available, scalable computational resources; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise. Results: We designed and implemented the Genomics Virtual Laboratory (GVL) as a middleware layer of machine images, cloud management tools, and online services that enable researchers to build arbitrarily sized compute clusters on demand, pre-populated with fully configured bioinformatics tools, reference datasets and workflow and visualisation options. The platform is flexible in that users can conduct analyses through web-based (Galaxy, RStudio, IPython Notebook) or command-line interfaces, and add/remove compute nodes and data resources as required. Best-practice tutorials and protocols provide a path from introductory training to practice. The GVL is available on the OpenStack-based Australian Research Cloud (http://nectar.org.au) and the Amazon Web Services cloud. The principles, implementation and build process are designed to be cloud-agnostic. Conclusions: This paper provides a blueprint for the design and implementation of a cloud-based Genomics Virtual Laboratory. We discuss scope, design considerations and technical and logistical constraints, and explore the value added to the research community through the suite of services and resources provided by our implementation.