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.
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.
Additional information is available at
http://www.agu.org/meetings/ja08/?content=program. We hope that you will
consider a contribution to this session.
Thank you,
Barbara Eckman and Lloyd Treinish
IBM Big Green Innovations
--------------------------
Lloyd A. Treinish
Project Scientist, Big Green Innovations
IBM Systems & Technology Group
1101 Kitchawan Road, Yorktown Heights, NY 10598
914-945-2770, lloydt@xxxxxxxxxx
http://www.research.ibm.com/people/l/lloydt/
http://www.research.ibm.com/weather/DT.html
http://www.ibm.com/technology/greeninnovations
