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This is a timely book presenting an overview of the current state-of-the-art within established projects, presenting many different aspects of workflow from users to tool builders. It provides an overview of active research, from a number of different perspectives. It includes theoretical aspects of workflow and deals with workflow for e-Science as opposed to e-Commerce. The topics covered will be of interest to a wide range of practitioners.
Scientific workflows have emerged as a key technology that assists scientists with the design, management, execution, sharing and reuse of in silico experiments. Workflow management systems simplify the management of scientific workflows by providing graphical interfaces for their development, monitoring and analysis. Nowadays, e-Science combines such workflow management systems with large-scale data and computing resources into complex research infrastructures. For instance, e-Science allows the conveyance of best practice research in collaborations by providing workflow repositories, which facilitate the sharing and reuse of scientific workflows. However, scientists are still faced with different limitations while reusing workflows. One of the most common challenges they meet is the need to select appropriate applications and their individual execution parameters. If scientists do not want to rely on default or experience-based parameters, the best-effort option is to test different workflow set-ups using either trial and error approaches or parameter sweeps. Both methods may be inefficient or time consuming respectively, especially when tuning a large number of parameters. Therefore, scientists require an effective and efficient mechanism that automatically tests different workflow set-ups in an intelligent way and will help them to improve their scientific results. This thesis addresses the limitation described above by defining and implementing an approach for the optimization of scientific workflows. In the course of this work, scientists’ needs are investigated and requirements are formulated resulting in an appropriate optimization concept. In a following step, this concept is prototypically implemented by extending a workflow management system with an optimization framework, including general mechanisms required to conduct workflow optimization. As optimization is an ongoing research topic, different algorithms are provided by pluggable extensions (plugins) that can be loosely coupled with the framework, resulting in a generic and quickly extendable system. In this thesis, an exemplary plugin is introduced which applies a Genetic Algorithm for parameter optimization. In order to accelerate and therefore make workflow optimization feasible at all, e-Science infrastructures are utilized for the parallel execution of scientific workflows. This is empowered by additional extensions enabling the execution of applications and workflows on distributed computing resources. The actual implementation and therewith the general approach of workflow optimization is experimentally verified by four use cases in the life science domain. All workflows were significantly improved, which demonstrates the advantage of the proposed workflow optimization. Finally, a new collaboration-based approach is introduced that harnesses optimization provenance to make optimization faster and more robust in the future.
This guidebook on e-science presents real-world examples of practices and applications, demonstrating how a range of computational technologies and tools can be employed to build essential infrastructures supporting next-generation scientific research. Each chapter provides introductory material on core concepts and principles, as well as descriptions and discussions of relevant e-science methodologies, architectures, tools, systems, services and frameworks. Features: includes contributions from an international selection of preeminent e-science experts and practitioners; discusses use of mainstream grid computing and peer-to-peer grid technology for “open” research and resource sharing in scientific research; presents varied methods for data management in data-intensive research; investigates issues of e-infrastructure interoperability, security, trust and privacy for collaborative research; examines workflow technology for the automation of scientific processes; describes applications of e-science.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Provenance and Annotation Workshop, IPAW 2008, held in Salt Lake City, UT, USA, in June 2007. The 14 revised full papers and 15 revised short and demo papers presented together with 2 keynote lectures were carefully reviewed and selected from 40 submissions. The paper are organized in topical sections on provenance: models and querying; provenance: visualization, failures, identity; provenance and workflows; provenance for streams and collaboration; and applications.
Workflow is Oracle's E-Business Suite tool for modeling business processes. Workflow combines procedures performed by the computer with a system of notifications that allow humans to better direct the computer how to proceed. This book provides a very thorough explanation of the various components of Workflow. You'll learn step by step how to develop and test custom Workflows, and how to administer Workflow using OAM, the Workflow Management screens, and Oracle Diagnostics. This book also explains how the underlying tables store the data generated by Workflow, and how to perform the setups required for a few of the most commonly used Oracle Workflows. The book also includes SQL scripts and sample procedures that we use at Solution Beacon to assess and solve Workflow problems, as well as DBA topics like cloning considerations and partitioning Workflow objects.
This book constitutes the thoroughly refereed proceedings of the First International Conference on InformationTechnology in Bio- and Medical Informatics, held in Bilbao, Spain, in September 2010. The 14 selected long papers and 8 selected short papers are divided in the following groups:Workflow management and database; Decision support and data management in biomedicine; Medical data modelling and information retrieval; Data mining in bioinformatics; Knowledge representation and data management in bioinformatics; Biological data and signal processing.
This book constitutes the refereed proceedings of the Third International Workshop on Data Integration in the Life Sciences, DILS 2006, held in Hinxton, UK in July 2006. Presents 19 revised full papers and 4 revised short papers together with 2 keynote talks, addressing current issues in data integration from the life science point of view. The papers are organized in topical sections on data integration, text mining, systems, and workflow.
This book offers a comprehensive introduction to workflow management, the management of business processes with information technology. By defining, analyzing, and redesigning an organization's resources and operations, workflow management systems ensure that the right information reaches the right person or computer application at the right time. The book provides a basic overview of workflow terminology and organization, as well as detailed coverage of workflow modeling with Petri nets. Because Petri nets make definitions easier to understand for nonexperts, they facilitate communication between designers and users. The book includes a chapter of case studies, review exercises, and a glossary. A special Web site developed by the authors, www.workflowcourse.com, features animation, interactive examples, lecture materials, exercises and solutions, relevant links, and other valuable resources for the classroom.
This book constitutes the thoroughly refereed post-proceedings of the Second European AcrossGrid Conference, AxGrids 2004, held in Nicosia, Cyprus in January 2004. The 27 revised full papers and 4 revised short papers presented were carefully selected during two rounds of reviewing and improvement from 57 submissions. The papers address the entire range of current topics in grid computing from computational and data grids to the semantic grid and grid application in various fields.
The amount of data in everyday life has been exploding. This data increase has been especially significant in scientific fields, where substantial amounts of data must be captured, communicated, aggregated, stored, and analyzed. Cloud Computing with e-Science Applications explains how cloud computing can improve data management in data-heavy fields such as bioinformatics, earth science, and computer science. The book begins with an overview of cloud models supplied by the National Institute of Standards and Technology (NIST), and then: Discusses the challenges imposed by big data on scientific data infrastructures, including security and trust issues Covers vulnerabilities such as data theft or loss, privacy concerns, infected applications, threats in virtualization, and cross-virtual machine attack Describes the implementation of workflows in clouds, proposing an architecture composed of two layers—platform and application Details infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) solutions based on public, private, and hybrid cloud computing models Demonstrates how cloud computing aids in resource control, vertical and horizontal scalability, interoperability, and adaptive scheduling Featuring significant contributions from research centers, universities, and industries worldwide, Cloud Computing with e-Science Applications presents innovative cloud migration methodologies applicable to a variety of fields where large data sets are produced. The book provides the scientific community with an essential reference for moving applications to the cloud.