[ESIP-all] AGU Session IN20: Scientific Workflows and Provenance: Strategies for Current and Emerging Issues

[Hua, Hook (388C)]

Dear Colleagues,

We are pleased to announce the following session for the Fall 2010 American
Geophysical Union (AGU) Meeting in December 13-17:

IN20: Scientific Workflows and Provenance: Strategies for Current and
Emerging Issues 
http://www.agu.org/meetings/fm10/program/scientific_session_search.php?show=
detail&sessid=442

Please consider submitting an abstract and forwarding this announcement to
potentially interested colleagues.

Description: Data are central to Earth and space science. Sharing,
understanding, and using such data leads to many questions. Where did the
data come from?  How was it created?  What am I allowed to do with it?  How
can I collaborate with my partners in using it?  This session will focus on
three emerging issues, briefly described below, that surround the use of
data in science: Semantics, Distributed Workflows, Provenance and the Ethics
of Data.  Formal encoding of vocabularies and content provision are now
emerging are a requirement in web-based information environments. A
significant opportunity exists to bring community support and endorsement to
such capabilities as well as exposing requirements for software development.
Linking knowledge and data sources often leads to distributed workflows,
with challenges in interoperability, automated construction, cloud-based
workflows, distributed provenance, and other emerging issues.   Providing
thorough provenance information, sufficient to guarantee that it is possible
to understand and reproduce a data set adds to the credibility and
usefulness of the entire measurement and data processing effort.  People
increasingly repurpose data in ways unforeseen and unforeseeable by the
original investigator or user community. This data sharing and reuse imply
certain ethical obligations for both data producers and users. These
obligations include ensuring that data are shared openly and preserved for
future generations, that data authors receive fair attribution, that data
are as accurate as possible, that data is reproducible, that uncertainty is
well described, and that data are not used inappropriately.

The submission deadline for abstracts is September 2, 2010.


Hook Hua, NASA/JPL
Deborah McGuinness, Rensselaer Polytechnic Institute, McGuinness Associates
Christopher Lynnes, NASA/GSFC
Brian Wilson, NASA/JPL