Workflow

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

Guidelines for using Bsoft for high resolution reconstruction and validation of biomolecular structures from electron micrographs

Abstract: Cryo-electron microscopy (cryoEM) is becoming popular as a tool to solve biomolecular structures with the recent availability of direct electron detectors allowing automated acquisition of high resolution data. The Bsoft software package, developed over 20 years for analyzing electron micrographs, offers a full workflow for validated single particle analysis with extensive functionality, enabling customization for specific cases. With the increasing use of cryoEM and its automation, proper validation of the results is a bigger concern. The three major validation approaches, independent data sets, resolution-limited processing, and coherence testing, can be incorporated into any Bsoft workflow. Here, the main workflow is divided into four phases: (i) micrograph preprocessing, (ii) particle picking, (iii) particle alignment and reconstruction, and (iv) interpretation. Each of these phases represents a conceptual unit that can be automated, followed by a check point to assess the results. The aim in the first three phases is to reconstruct one or more validated maps at the best resolution possible. Map interpretation then involves identification of components, segmentation, quantification, and modeling. The algorithms in Bsoft are well established, with future plans focused on ease of use, automation and institutionalizing validation.

An agent-based Web service workflow model for inter-enterprise collaboration

Abstract: The service-orientated computing paradigm is transforming traditional workflow management from a close and centralized control system into a worldwide dynamic business process. A complete workflow serving inter-enterprise collaboration should include both internal processes and ad hoc external processes. This paper presents an agent-based workflow model to address this challenge. In the proposed model, agent-based technology provides the workflow coordination at both inter- and intra-enterprise levels while Web service-based technology provides infrastructures for messaging, service description and workflow enactment. A proof-of-concept prototype system simulating the order entry, partner search and selection, and contracting in a virtual enterprise creation scenario is implemented to demonstrate the dynamic workflow definition and execution for inter-enterprise collaboration.

Mining of ad-hoc business processes with TeamLog

Abstract: The design of workflows is a complicated task. In those cases where the control flow between activities cannot be modeled in advance but simply occurs during enactment time (run time), we speak of ad-hoc processes. Ad-hoc processes allow for the flexibility needed in real-life business processes. Since ad-hoc processes are highly dynamic, they represent one of the most difficult challenges, both, technically and conceptually. Caramba is one of the few process-aware collaboration systems allowing for ad-hoc processes. Unlike in classical workflow systems, the users are no longer restricted by the system. Therefore, it is interesting to study the actual way people and organizations work. In this paper, we propose process mining techniques and tools to analyze ad-hoc processes. We introduce process mining, discuss the concept of mining in the context of ad-hoc processes, and demonstrate a concrete application of the concept using Caramba, process mining tools such as EMiT and MinSoN, and a newly developed extraction tool named Teamlog.

Opportunities and Challenges in Running Scientific Workflows on the Cloud

Abstract: Cloud computing is gaining tremendous momentum in both academia and industry. The application of Cloud computing, however, has mostly focused on Web applications and business applications; while the recognition of using Cloud computing to support large-scale workflows, especially data-intensive scientific workflows on the Cloud is still largely overlooked. We coin the term "Cloud Workflow", to refer to the specification, execution, provenance tracking of large-scale scientific workflows, as well as the management of data and computing resources to enable the execution of scientific workflows on the Cloud. In this paper, we analyze why there has been such a gap between the two technologies, and what it means to bring Cloud and workflow together; we then present the key challenges in running Cloud workflow, and discuss the research opportunities in realizing workflows on the Cloud.