<br><font size=2 face="sans-serif">In case you have not heard, we are chairing
a session on Frameworks for Environmental Data Integration, Modeling and
Analysis at the upcoming AGU Joint Assembly in May in Fort Lauderdale.
In particular, we are soliciting contributions from diverse, multi-disciplinary
developer and user groups within the AGU community, particularly with experience
in both the scientific and technological issues in data model, management
and archive systems, model development, observing systems, data analysis
and assimilation, visualization, standards activities, and community software
and data set development and support.</font>
<br>
<br><font size=2 face="sans-serif">As background, consider that frameworks
to support environmental data exchange and integration associated with
modeling and analysis have recently been proposed in the Earth and Space
Science community. This notion should be extended beyond the enabling
computing technology and infrastructure to address any data generator.
Hence, output from sensors (in situ and remote), simulations, analyses
(e.g., data assimilation), visualization, etc. need to be treated in an
uniform fashion, for which data exchange and coupling need to be addressed.
This session is intended to provide a forum for sharing algorithms,
techniques, experience and best practices across such diverse considerations
for which there is underlying commonality but not necessarily collaboration
to date. As you know, many research activities and operational decisions
in environmental sciences require extensive computational modeling and
data analysis. Hence, questions of critical importance often require
multiple models to be coupled, running either sequentially or in parallel,
and the results compared to or integrated with observational data sets.
But the approach needs to focus on the rationale behind such questions
and recognize the technology as an enabler. For example, predicting
the impact of certain land use decisions in a river basin might involve
the coupling of water balance, water quality, carbon storage, crop production,
and biodiversity models. Prediction of impacts of global climate
change on flooding patterns might involve perturbing numerical weather
predictions, and coupling them to hydrological calculations based upon
results of ensembles of climate models. While the experience behind
extant frameworks and data models is critical to this session, an important
goal is to identify methodologies that can be more generalized and avoid
a tight coupling between data representation and the architectures behind
computation or observation (e.g., being able to capture the semantics of
the data to enable proper utilization). A further result will be
recommendations for both research and development activities as well as
case studies to help evaluate the methodologies that are identified.</font>
<br>
<br><font size=2 face="sans-serif">Additional information is available
at http://www.agu.org/meetings/ja08/?content=program. We hope that
you will consider a contribution to this session.</font>
<br>
<br><font size=2 face="sans-serif">Thank you,</font>
<br><font size=2 face="sans-serif">Barbara Eckman and Lloyd Treinish</font>
<br><font size=2 face="sans-serif">IBM Big Green Innovations</font>
<br><font size=2 face="sans-serif"><br>
--------------------------<br>
Lloyd A. Treinish<br>
Project Scientist, Big Green Innovations<br>
IBM Systems & Technology Group<br>
1101 Kitchawan Road, Yorktown Heights, NY 10598<br>
914-945-2770, lloydt@us.ibm.com<br>
http://www.research.ibm.com/people/l/lloydt/<br>
http://www.research.ibm.com/weather/DT.html<br>
http://www.ibm.com/technology/greeninnovations</font>