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Introduction

Data Intensive Workflows (a.k.a. scientific workflows) are routinely used in most scientific disciplines today, especially in the context of parallel and distributed computing. Workflows provide a systematic way of describing the analysis and rely on workflow management systems to execute the complex analyses on a variety of distributed resources. This workshop focuses on the many facets of data-intensive workflow management systems, ranging from job execution to service management and the coordination of data, service and job dependencies. The workshop therefore covers a broad range of issues in the scientific workflow lifecycle that include: data intensive workflows representation and enactment; designing workflow composition interfaces; workflow mapping techniques that may optimize the execution of the workflow; workflow enactment engines that need to deal with failures in the application and execution environment; and a number of computer science problems related to scientific workflows such as semantic technologies, compiler methods, fault detection and tolerance.

Call for paper

Submission Topics

The topics of the workshop include but are not limited to: Big Data analytics Workflows Data-driven workflow processing Workflow composition, tools and languages Workflow execution in distributed environments Workflows on the cloud Exascale computing with workflows Workflow refinement tools that can manage the workflow mapping process Workflow fault-tolerance and recovery techniques Workflow user environments, including portals Workflow applications and their requirements Adaptive workflows Workflow monitoring Workflow optimizations Performance analysis of workflows Workflow debugging Workflow provenance Interactive workflows Workflow interoperability
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Important Date
  • Nov 16

    2014

    Conference Date

  • Nov 16 2014

    Registration deadline

Sponsored By
Association for Computing Machinery - ACM