This is a repost from a recent message to DBWORLD:
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C A L L F O R P A P E R S
SIGMOD RECORD, September 2005 Issue
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Special Section on Scientific Workflows
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Guest editors:
Bertram Ludaescher & Carole Goble
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Today computational scientists across all disciplines (from biology, medicine,
ecology, and other life sciences to chemistry, physics, geosciences, and
astronomy) create ever increasing amounts of often highly complex
data. Generated raw and derived data may come from wet lab experiments
(possibly under control of a LIMS), large-scale data-intensive and
compute-intensive simulations, or real-time observations e.g. from remote
sensors. Technical challenges include not only the volume of data, but also
the complexity of data of "metadata-intensive" applications.
In order to support scientists in their data management and analysis tasks,
scientific workflows have recently gained increased interest and momentum as a
unifying mechanism for handling scientific data. While loosely related to the
more traditional business workflows studied earlier by the database community,
scientific workflows pose a quite different set of challenges due to the
special nature of scientific data and the specific needs for large-scale data
collection, querying, analysis, and visualization. Scientific workflows are
often designed or depicted in a block diagram style, with connections
indicating data-flow (and sometimes control-flow) between individual tasks.
A comprehensive scientific workflow system should be able to schedule workflow
tasks (typically in a distributed/Grid environment), monitor and control
execution, allow on-the-fly visualization and computational steering, support
user-interaction, facilitate "pause & rerun" of workflows, keep track of data
provenance, and support various static and dynamic analysis and optimization
techniques. Moreover, the underlying scientific workflow model and paradigm
should facilitate component and subworkflow reuse.
We invite contributions on all aspects of database technologies for scientific
workflows (SWFs) including but not limited to:
- conceptual modeling and design of SWFs
- computation models for SWFs
- scheduling, resource allocation, and planning for SWFs
- static analysis, validation, verification of SWFs
- distributed and Grid-based SWFs
- web-service based SWFs (incl. overcoming limitations of web services)
- data-intensive, compute-intensive, metadata-intensive SWF applications
- data mining, data analysis, and statistics in SWFs
- highly interactive SWFs
- long running and non-interactive SWFs
- transaction management and SWFs
- fault tolerance in SWFs
- scientific visualization and SWFs
- problem-solving environments for SWFs (scientific workflow systems)
- coupling SWF systems with other systems (databases, LIMS, statistics
packages, visualization tools, etc)
- data and workflow provenance in SWFs
- knowledge representation and semantic extensions to SWFs
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IMPORTANT DATES:
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Paper submission deadline : May 21th, 2005
Notification of acceptance: June 26th, 2005
Camera ready copies due : July 10th, 2005
Submitted articles should not exceed 6 pages in the 2-column, 10-point SIGMOD
Record format (see http://www.sigmod.org/record/author.html)
Please email your contributions in PDF format, using
Subject: SIGMOD-Record/SWF
to LUDAESCH(a)UCDAVIS.EDU.
--
Bertram Ludaescher
Dept. of Computer Science & UC Davis Genome Center
University of California at Davis
One Shields Avenue, Davis, CA 95616
530-754-8576 (ph), 530-752-4767 (fax)
ludaesch(a)ucdavis.edu
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