WORKS'12 CfP

                     The 7th Workshop on Workflows in Support of
Large-Scale Science
                                                   in conjunction with SC 12

http://works.cs.cardiff.ac.uk

                                                         Call For Papers

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Data Intensive Workflows (a.k.a. scientific workflows) are a key technology
that enable the set
up of large data sets analysis experiments in all scientific areas,
exploiting capabilities of
large-scale distributed and parallel computing infrastructures. Workflows
enable scientists to
design complex analysis that are composed of individual application
components or services
and often such components and services are designed, developed, and tested
collaboratively.

On large-scale computing infrastructures routinely used for e-Sciences
today, workflow
management systems provide both a formal description of distributed
processes and an engine
to enact applications composed of wealth of concurrent processes.

The size of the data and the scale of the data analysis flows often lead to
complex and
distributed data sets management. Workflow formalisms including adequate
structures for
data sets representation and concurrent processing are needed. Besides the
magnitude of data
processed by the workflow components, the intermediate and resulting data
needs to be
annotated with provenance and other information to evaluate the quality of
the data and
support the repeatability of the analysis.

The process of workflow design and execution in a distributed environment
can be very
complex and can involve multiple stages including their textual or
graphical specification, the
mapping of the high-level workflow descriptions onto the available
resources, as well as
monitoring and debugging of the subsequent execution.  Further, since
computations and data
access operations are performed on shared resources, there is an increased
interest in
managing the fair allocation and management of those resources at the
workflow level.

Data-driven computations are increasingly considered to tackle the wealth
of data generated
by scientific instruments. Yet, scientific experiments also require the
description of complex
control flows. Adequate workflow descriptions are needed to support the
complex workflow
management process, which includes workflow creation, workflow reuse, and
modifications
made to the workflow over time—for example modifications to the individual
workflow
components. Additional workflow annotations may provide guidelines and
requirements for
resource mapping and execution.

The Seventh Workshop on Workflows in Support of Large-Scale Science focuses
on the entire
workflow lifecycle including the workflow composition, mapping, robust
execution and the
recording of provenance information.  The workshop also welcomes
contributions in the
applications area, where the requirements on the workflow management
systems can be
derived. The topics of the workshop include but are not limited to:
  - Data Intensive 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.
  - Mashups and workflows.

Important Dates:
  - Papers due September 7, 2012
  - Notifications of acceptance October 5, 2012
  - Final papers due October 19, 2012

Program Committee Chairs:
  Johan Montagnat, CNRS, France
  Ian Taylor, Cardiff University, UK

Program Committee Members:
  Khalid Belhajjame     University of Manchester
  Adam Belloum  University of Amsterdam
  Ivona Brandic         Vienna University of Technology
  Marian Bubak          AGH Krakow & University of Amsterdam
  Ann Chervenak University of Southern California
  Ewa Deelman           USC Information Sciences Institute
  Tristan Glatard       CNRS
  Andrew Harrison       Cardiff University
  Péter Kacsuk          MTA SZTAKI
  Dimka Karastoyanova   Stuttgart University
  Daniel S. Katz                University of Chicago & Argonne National
Laboratory
  Tamas Kiss            University of Westminster
  Dagmar Krefting       University of Applied Sciences Berlin
  Maciej Malawski       AGH University of Science and Technology
  Stephen McGough       Newcastle University
  Gaurang Mehta Universirty of Southern California
  Jarek Nabrzyski       Univeristy of Notre Dame
  Cesare Pautasso       University of Lugano
  Radu Prodan           University of Innsbruck
  Omer Rana             Cardiff University
  David De Roure        Oxford University
  Rizos Sakellariou     University of Manchester
  Gabor Terstyanszky    University of Westminster
  David Walker          Cardiff University
  Michael Wilde         University of Chicago & Argonne National Laboratory
  Qishi Wu                      University of Memphis