[ESIP-all] FW: Information Systems Sessions AGU Fall Meeting
Carol B. Meyer
carol.meyer at earthsciencefoundation.org
Tue Aug 9 09:13:01 EDT 2005
Please see the message below from Robin Pfister
-----Original Message-----
From: Robin Pfister [mailto:robin.g.pfister at nasa.gov]
Sent: Tuesday, August 09, 2005 8:00 AM
To: carol.meyer at earthsciencefoundation.org
Cc: pfister at gsfc.nasa.gov
Subject: Information Systems Sessions AGU Fall Meeting
Folks,
The Fall 2005 AGU meeting will be an exciting one for the new Earth and
space Science Informatics (ESSI) Focus Group. There are a number of
intriguing session topics that will generate lots of interest and good
discussion at the meeting. Please notify your colleagues and and
encourage their participation. A list of sessions is summarized below,
followed by session abstracts. Please consider submitting abstracts to
describe your efforts http://www.agu.org
Upcoming key dates:
July 26: Abstract Submissions Tool Opens
September 1: Postal Mail Abstract Deadline
September 8: Electronic Submission Abstract Deadline
(After this date, AGU will allot oral slots and room assignments and
perform scheduling.)
October 17: Acceptance letters to Presenters and Chairs
Oct 20: Program Posted on AGU Website
November 3: Pre-Registration Deadline and Housing Deadline
November 10: Registration Deadline
December 5-9 Fall Meeting!
Looking forward to seeing you all this fall in San Francisco!!!
Bernard Minster ESSI Chair
Robin Pfister ESSI Vice-Chair
1. Earth and Space Science Informatics General Contributions
2. Intelligent and Adaptive Systems for Data Collection, Processing, and
Knowledge Discovery
3. Emerging Better, or Best, Practices for Distributed Data Systems and
Virtual Observatories
4. Frontiers in Remote Sensing and Space-Based Earth System Observations
5. Emerging Technology for Environmental Sensor Networks
6. Advances and trends in Biogeophysical, Ecological, and Related Data
Collection, Analysis, Archiving, and Distribution
7. Building a Global Geoscience Cyberinfrastructure: International
Collaboration in Geoinformatics
8. Transforming Geoscience Access Through Standards Implementation
9. Web-based Service Oriented Earth Science
10. Ontologies for Earth and Space Sciences
11. Community Approaches to Data Sharing
12. Statistical Treatment of Analytical and Synthetic Data in Earth
Sciences: Moving From the Qualitative to the Quantitative
13. Analysis and Representation of Geophysical Data on the Sphere
14. Data Fusion
15. Multidisciplinary Global Modeling -- Moving Towards the Really Big
Picture
16. Visualization of Large Data Sets in Earth Space Sciences
1. Earth and Space Science Informatics (ESSI) General Contributions
(NOTE: this is a catch-all for miscellaneous submissions that don't fall
into one of the existing sessions)
J. Bernard Minster
Robin Pfister
This session provides the opportunity for contributions that fall
within the broad spectrum of Earth and Space Science Informatics, but
are not appropriate in any of the other approved Sessions.
2. Intelligent and Adaptive Systems for Data Collection, Processing, and
Knowledge Discovery
Alexander, Susan E California State University Monterey Bay
Bredekamp, Joseph H NASA HQ
Conover, Helen University of Alabama in Huntsville
Coughlan, Joseph C NASA
Graves, Sara J University of Alabama in Huntsville
Ramachandran, Rahul University of Alabama in Huntsville
The enormous volume of science data being collected and archived by
different agencies has necessitated the current focus on technologies
and infrastructure for implementing and scaling up scientific data
acquisition, management and dissemination. There are complementary
methods needed to make data collection systems and modular modeling
frameworks more robust such that they are easy to construct and modify,
require less human intervention to operate and produce fewer errors.
Traditionally these capabilities come from the interdisciplinary
collaboration of computational, Earth and space scientists. As data
collection and management continues to require greater knowledge of
computing, the need to make these systems "smarter" and adaptive to new
scenarios is a research topic under study by mission-oriented
organizations such as NASA and DARPA. One technique that can be
employed in these intelligent systems is data driven knowledge
discovery. This approach brings to bear techniques and algorithms from
the fields of machine learning, statistics, databases, expert systems,
pattern recognition and data visualization to rapidly analyze and
explore these heterogeneous data sets with the goal of discovering
knowledge, which can trigger further action.
Diverse examples of intelligent and adaptive systems are appearing, and
these technologies are utilized by a growing number of data providers
and mission data systems in the planetary, Earth and astronomical
sciences. Examples are the Mars Exploration Rover Mission, Virtual
Observatory and Earth System Information Partners. The goal of this
special session is to gather practitioners of such techniques and
provide them a venue to share their work with others. Therefore, this
session will solicit not only papers on successful application of these
techniques on various science problems but also papers discussing:
limitations of such techniques; challenges of applying them to science
problems; and finally the future research directions in this area.
3. Emerging Better, or Best, Practices for Distributed Data Systems and
Virtual Observatories
Fox, Peter HAO/ESSL/NCAR
Papitashvili, Vladimir University of Michigan
Roberts, Aaron GSFC/NASA
It is now at least 5 years since the virtual observatory (VO) paradigm
appeared and about 15 years since distributed data systems (DDS) started
appearing. These efforts have produced numerous successes, failures,
lessons, new concepts, new designs, and copious experience with changing
technologies. Science communities and agencies stand ready to utilize
these concepts to their fullest extent in meeting the challenging
explosion of data from instruments and models in the present and next
decade.
However many questions remain:
-Are VOs (or an analog paradigm in fields where 'observatories' are not
the usual construct) changing, or ready to change, the way our
communities perform sicence on ever increasing amounts and diversity of
data?
-How can heterogeneous and distributed data systems be created, found,
accessed and lead to new science and understanding?
-How can proper attribution of sources of data be made and tracked in a
data-world that is increasingly 'virtual'?
-How can educators make use of VOs and DDSs that were designed for
experts to use?
To address these questions, this session features contributions from
those involved in VOs and DDS at all levels: science and
education/outreach developers/users, interdiscplinary researchers,
designers/architects, developers, and data providers to contribute their
experiences under the theme of emerging better and where appropriate,
best practices.
4. Frontiers in Remote Sensing and Space-Based Earth System Observations
Albjerg, Marian NASA Earth-Sun System Technology Office
Prescott, Glenn NASA Earth-Sun System Technology Office
Many promising remote sensing technologies and systems of space-based
observations will be bringing scientific data and observations to Earth
scientists in the next 5 to 10 years. These include instruments such as
passive and active microwave and optical sensors for measuring
geophysical parameters of the atmosphere, the seas and the land masses.
This session, which is hosted by the NASA Earth Sun System Technology
Office, solicits papers relating to the broad range of instrument
technologies that support earth science observations.
5. Emerging Technology for Environmental Sensor Networks
Bellingham, James Monterey Bay Aquarium Research Institute
Hart, Jane Karen Unversity of Southampton
Martinez, Kirk University of Southampton
Palo, Scott University of Colorado
Environmental Sensor Networks are a new way of monitoring the
environment. They comprise autonomous sensor nodes which are placed in
the environment and automatically record real-time data, which is then
transmitted, typically via a base station, to a data server. There the
data can be integrated with other data sets (i.e. satellite images, GIS,
processes models). Such autonomous distributed sensor networks offer
great promise for improving spatial and temporal coverage in harsh
environments such as the Arctic and Antarctic, global oceans and severe
storms. These networks are used both to understand environmental
processes and/or act as intelligent hazard warning systems. There are
three vital research areas in this field which we wish to address in
this special session: a) sensor node design including vehicles such as
autonomous underwater and aerial vehicles (AUV & UAV), b) telemetry and
networking and c) cyberinfrastructure, including data management, event
detection and response, and the creation of assimilative models for data
synthesis and prediction. Speakers will discuss these themes as well as
overall system designs. This will be a chance for Earth and Space System
Scientists to exchange ideas with the communication network designers,
to share the successes and problems of constructing working
Environmental Sensor Networks from a range of environments.
6. Advances and Trends in Biogeophysical, Ecological, and Related Data
Collection, Analysis, Archiving, and Distribution
Billesbach, Dave University of Nebraska-Lincoln
Gentry, Merilyn J NASA LBA Data Coordinator
As technology has advanced, the underlying methodology and paradigms of
biogeophysical, ecological, and related research have changed in
response. Previously, the functions of in-field data collection, data
reduction and analysis, data archiving, and distribution and re-use were
separate and distinct. Now, however the lines between them have become
blurred. Additionally, as we have gained the ability to generate
ever-larger quantities of data, we are seeking to minimize the amount of
time that humans spend interacting with that data and the instruments
that generate them. Some examples of these trends are remotely operated
flux towers, automated QA/QC procedures, advanced search techniques, and
distributed archival systems. Despite the progress made, many of these
research sites are not and probably will never be considered
"autonomous". Lessons have been learned from both small individual
investigator experiments and from large collaborative efforts (i.e.
FIFE, BOREAS, LBA, SAHARA-2000, AmeriFlux, etc.). Some of these lessons
have been incorporated into funding agency guidelines for documentation
(metadata), quality assurance, and data delivery (to archive centers),
as well as suggestions for sensor selection and temporal and spatial
measurement grids. More of this experience, however, must be
incorporated into the design of future research efforts to insure
long-term and global availability and usability of the data sets.
In this forum, we seek contributions from data generators (field
scientists), data users (modelers), and data managers that explore the
current technology and trends in these areas, and anticipate future
needs. THIS IS A POSTER SESSION ONLY.
7. Building a Global Geoscience Cyberinfrastructure: International
Collaboration in Geoinformatics
Keller, George Randy University of Texas at El Paso
Klump, Jens GeoForschungsZentrum Potsdam
Lehnert, Kerstin A. Lamont-Doherty Earth Observatory, Columbia
University
Snyder, Walter S. Boise State University
Geoscience is a global science. The emerging Geoscience
cyberinfrastructure must be an international effort in order to
successfully promote advances in geoscience research and enable new
approaches to addressing scientific problems that in turn lead to new
discoveries and an improved understanding of the Earth. In many
countries around the globe, a rapidly increasing number of Geoscience
projects are developing and maintaining digital data and information
systems together with tools for data analysis and visualization. In
order to maximize the impact of these globally distributed
Geoinformatics resources, it is essential that these efforts be
collaborative and integrated. This sessions focuses on this
collaboration and integration.
The session has two objectives: (1) to draw attention to and discuss the
many political, cultural, organizational, and technical challenges that
need to be addressed and overcome in order to achieve a truly global
cyberinfrastructure for the Geosciences. Examples include: How does the
global community get connected and stay connected? What are the
advantages/disadvantages of an open and distributed system versus a more
centrally run system? What 'standards' do we need, how can we implement
them? What are the different funding scenarios, and how can
international collaboration be supported? (2) to highlight examples of
international collaborations that successfully coordinate and integrate
their efforts.
8. Transforming Geoscience Access Through Standards Implementation
Cole, Marge NASA/GST, Inc.
Yang, Chaowei Phil George Mason University
Open standards for geospatial data interoperability have reached a level
of maturity that enables broader integration of geoscience data
products, associated processing services, sensor webs, and analytical
Earth science models into solutions for society.
We encourage submission of papers describing geoscience applications,
research methods, strategic goals, or decision processes, enabled by
interoperable access to Earth science data, services, and models. We
are interested in the use of interoperability standards developed and or
recognized within the national and international standards bodies such
as FGDC, ANSI, and ISO. We also solicit reference to the standards
implementation process, use of the Geospatial Interoperability Reference
Model (GIRM) http://gai.fgdc.gov/girm/, and 3D visualizations. Our
interest extends to lessons learned, limitations, and enhancements to
these standards needed for greater access and use of Earth science data.
We are especially interested in the societal benefit areas identified in
the Global Earth Observation System of Systems and the U.S. Integrated
Earth Observation System, including agriculture, air quality, carbon
management, coastal management, disaster management, ecological
forecasting, energy, invasive species, public health, and water
management.
9. Web-Based Service-Oriented Earth Science
Berrick, Stephen NASA/GSFC
Halem, Milton University of Maryland, Baltimore County
Hardin, Danny The University of Alabama in Huntsville
Leptoukh, Gregory NASA/GSFC
Tilmes, Curt NASA/Goddard Space Flight Center
The emergence of affordable powerful computing clusters, low cost on
line mass disk storage capacity and information architectures allowing
encapsulation of high order scientific service requests are providing
new opportunities to access, process, visualize, analyze and model the
growing volume of Earth science data records by a broader science
community. This session solicits papers that present use cases of web
based services and simple to use interfaces utilizing scientifically
validated algorithms that enable (1) visualization and analysis, and
subsetting, convolving and gridding of multi-sensor radiance data
records, (2) generation of specialized Earth science data products, and
(3) invoking of regional and global models and parameterizations
initialized with operational or research derived data fields. Also
solicited are papers presenting (1) architectural solutions that address
extensibility and reusability of these services and interfaces, (2) data
representation and presentation options, and (3) examples of discovery,
composition and grid computing services that enhance research,
applications, and education.
10. Ontologies for Earth and Space Sciences
Fox, Peter HAO/ESSL/NCAR
Hurlburt, Neal Lockheed Martin Solar and Astrophysics Lab
McGuinness, Deborah Stanford University Knowledge Systems Lab
Raskin, Robert JPL/NASA
Knowledge representation and the accompanying formalism provided by
ontologies are the basis for efforts such as the semantic web and the
semantic grid. Knowledge representation is not new, but has been a
formal field of computer science research and applications for over 3
decades.
Ontologies have had relatively little exposure in the fields of Earth
and Space Sciences (ESS) and accordingly less development and
applications built upon them. In contrast, other fields have produced
biomedical and gene ontology efforts and have demonstrated value using
ontology-based technology for scientific applications. They also have
experience evaluating capabilities and limitations, developed new
concepts, and new designs, and have copious experience with changing
technologies.
Science communities and agencies stand ready to utilize these concepts
to their fullest extent in meeting the challenging explosion of data
from instruments and models in the present and next decade(s). The
session features a series of invited presentations including:
introduction to ontologies, experience with ontologies in fields other
than ESS, and what is currently developed or planned for ESS. The aim is
to introduce and explain knowledge representation, semantics and
ontologies to the AGU community and discuss opportunities of how
knowledge representation technologies can change the way our communities
develop interdisciplinary and diverse science applications, enable new
science and help educators.
Both Oral and Poster contributions are sought from those with an
interest in semantically-enabled computer applications spanning all
fields in ESS (education, data, models, assimilation, etc.) as well as
those actively involved in knowledge representation research and/or
applications, ontology development and/or use and practitioners
supporting or designing science applications (e.g. Virtual
Observatories, Distributed Data Systems, and so on).
11. Community Approaches to Data Sharing
Hankin, Steven C. NOAA / Pacific Marine Environmental Laboratory
Ullman, Richard E. NASA / Goddard Space Flight Center
Today's increasingly interdisciplinary science environment demands
expanded data access and broad data sharing. Scientists are now expected
to share data not only with colleagues in their own departments and
discipline community, but also to make data generally available and
accessible for use in distant contexts. Scientific communities routinely
adopt methods for sharing data among members of their own community.
These methods include any practice that makes data sharing more
effective such as use of industry standards, science content agreements,
common vocabularies, file naming conventions, interface or access
protocols file formats, gridding conventions, metadata practices, etc.
Leveraging and extending these data sharing methods not only enables
data exchange within communities of practice, but if documented, can be
used to build bridges to other communities. These practices and
bridges among them can contribute to the "system of systems" approach
advocated in US state and federal interagency initiatives and
international collaboration projects such as Virtual Observatories,
USGEO, IOOS and GEOSS among others. We invite papers on practices for
data interchange and interuse that build on 1) industry standards; or
(where those are inadequate) 2) supplement with broad community
practices (grass roots but moving up.)
12. Statistical Treatment of Analytical and Synthetic Data in Earth
Sciences: Moving >From the Qualitative to the Quantitative
Shragge, Jeffrey Chilver Stanford University
Snow, Cameron Allen Stanford University
During the past two decades the amount of geochemical data (major
element, trace-element, and isotopic) available to earth scientists has
exponentially increased. Furthermore, as analytical techniques have
became better refined and instrumentation better suited for geological
samples, the precision of such data has become extraordinarily precise.
However, much of this data is still treated qualitatively by the
geoscience community, and is often simply plotted onto diagrams to show
trends in the data, and not treated in a statistically rigorous manner.
For example, when statistics are computed for many of the diagrams,
values such as r-squared are often cited to show goodness of fit, but in
reality, there is not geologic meaning behind the statistics.
This session invites contributions that address the following topics:
- The statistical treatment of analytical data in the earth sciences
- The use of quantitative versus qualitative analysis of data sets
- The use of large geochemical databases to further understanding of
petrologic processes
- Geochemical discrimination and statistical theory
- Synthetic datasets in geochemistry
- Any other contribution that demonstrates the benefits of the
quantitative use of data, including proof-of-concept studies.
13. Analysis and Representation of Geophysical Data on the Sphere
Jackson, Andy University of Leeds
Simons, Frederik J University College London
Wieczorek, Mark Institut de Physique du Globe de Paris
Yuen, Dave University of Minnesota
Geodesy, Geomagnetism, Hydrology, Nonlinear Geophysics, Oceanography,
Planetary Science, Seismology: all of our subdisciplines share one
characteristic: the need for effective tools to collect and represent,
analyze and model data sets on the sphere (can you say GOCE? GRACE?
CHAMP?). Perhaps surprisingly, but methods for doing so are often
lacking. Wavelet analysis is one such example: well established in one-
and two-dimensional Cartesian geometry, wavelets on the sphere for the
most part still need to find their way from the applied mathematicians'
desk to the practitioners'. On the other hand, methods that are being
developed in one area of geophysics might be applicable to others.
The purpose of this session is to share our advances across the
disciplines. Contributions are sought on two fronts: 1) methodological
studies exposing innovative techniques for data analysis and
representation on the sphere, and 2) case studies of real-world
applications in which the application of new methods yield insights
previously unobtainable with standard Cartesian methods.
As the expected audience is broad, and hopefully large, we will focus on
submissions that highlight contributions from a cross-disciplinary
angle.
14. Data Fusion
Braverman, Amy Jet Propulsion Laboratory/Caltech
Tiampo, Kristy University of Western Ontario
This session invites submissions concerning all aspects of the
synergistic use of data from more than one source, both applications and
methodologies. This includes, but is not limited to statistical or
physical model-based methods including image analysis techniques, joint
retrievals, and simple case study examples using ad hoc procedures. We
are especially interested in applications to remote sensing and
corroborating, ground or in-situ data; for example: Earth Observing
System data used in combination with field campaign measurements.
However, we encourage submission from all areas of the geosciences again
including but not limited to seismology, astronomy/astrophysics,
planetary science, atmospheric science, climate change and variability,
land surface studies, cryosphere, natural hazards, weather, hydrology,
and ocean science.
15. Multidisciplinary Global Modeling: The Really Big Picture
Birk, Ronald J NASA, Applied Science, SMD
Collins, Bill CCSM,SSC, National Center for Atmospheric Research
Labelle-Hamer, Nettie Alaska Satellite Facility
Meier, Walter N. NSIDC-CIRES
True, Scott A. WGS R&D, Basic and Applied Research Office,National
Geospatial-Intelligence Agency
Weaver, Ronald L.S. NSIDC-CIRES
The Earth is a complex system driven by many physical processes.
Modeling these complex processes is as valuable as it is common in many
geophysical sciences. Each discipline of geophysics has traditionally
focused on limited sets of closely related phenomena using methodologies
and data sets optimized for its specific area of interest.
As the technology and methods of each discipline progress, scientists
have employed increasingly sophisticated means of isolating the signals
of interest from measurements that are influenced by many phenomena that
are "out-of-scope" for a particular study. The complexity of
simultaneously modeling all or a majority of the physical processes
affecting a given measurement has historically been extremely difficult
if not impossible with the available technology.
Times are changing. The computation, storage, and communication
capabilities of modern computer systems are growing rapidly. Modeling
practices considered impossibly complex 10 years ago are routine today.
The Internet and broadband communications have made available huge
stores of data useful for model initial and boundary conditions and
model validation. In the Earth sciences for example, NASA's Earth
Observing System has collected prodigious amounts of satellite-based
Earth observations over the past 10 years. The tantalizing promise for
the future is the possibility of multidisciplinary global modeling that
extracts the significant signals buried in the available measurements.
Geophysicists may someday have access to an integrated model of the
Earth system that is continually refined by ongoing measurements from
space, air, land, and sea sensors.
There are many technical obstacles to overcome before we can achieve
this ultra-model. Earth sensors (space, air, land or sea) need to be
more accurate and less expensive to build, deploy, and maintain. This
allows better coverage and resolution in the measurements. Sensor
platforms and data networks must be linked and the measurements placed
in formats and systems appropriate for both modeling and research.
Multidisciplinary teams need to be formed to start connecting and
integrating their models, as well as the data sets. New algorithms and
methodologies must be developed to build integrated models.
The primary goal of this session is to bring together scientists from
across the disciplines of geophysics for two important discussions: 1)
modelers-to-modelers sharing research into the science and technology
that will enable integrated global modeling and 2) modelers-to-data
managers to encourage increased use of Earth observation data in global
models.
Papers describing innovative techniques for parameterizing and
estimating integrated multidisciplinary global geophysical models as
well as for potential sharing of massive geophysical data sets to be
used in modeling are invited. We expect this session to involve a
dialogue on plans for optimizing the use of NASA, NOAA, and other open
national and international research results between the curators of
these data and modelers -- to the expressed end of increasing the usage
of these science data products to serve society through improved
analyses and predictions.
We expect the following questions to be addressed in this session:
>From the perspective of model techniques development:
-What modeling technologies and techniques have potential application
across multiple disciplines?
-What are the limitations of current modeling technologies and
techniques that constrain or prevent multidisciplinary modeling? What
can be done to overcome these limitations?
-What might the science communities do to promote multidisciplinary
global models of geophysical processes?
>From the perspective of data utilization in models:
-What are the current and future barriers to the use of observational
data in modeling?
-What tools are needed to translate and integrate observational data for
assimilation, boundary conditions, or validation?
-How can data managers address data quality issues in an optimal way for
modelers?
-How do modelers find out about data and data products? Are there more
efficient mechanisms possible?
-What are the key elements that data centers need to know about data
assimilation?
It is the intention of the conveners to include an open forum for
discussion of this topic during the course of this session and/or
through an ice breaker for data managers and modelers.
16. Visualization of Large Data Sets in Earth and Space Sciences
Donnellan, Andrea Jet Propulsion Laboratory
Erlebacher, Gordon Florida State University
Travis, Bryan Los Alamos National Laboratory
Yuen, David A. University of Minnesota
Researchers in the AGU community are faced relentlessly with numerical,
satellite, and experimental datasets of exponentially increasing size.
These datasets are stored on one or several servers geographically
distributed. Increasing collaborations between researchers throughout
the world motivates the use of shared resources, whether in the form of
computational grids, storage areas, visualization servers, or data
mining centers.
The goal of this ESSI session is to engender discussion among
researchers that employ modern tools of analysis, feature extraction,
visualization, and compression to ease the task of shared interaction
between geographically distributed researchers. Contributions are sought
in areas of nonlinear geophysics that cover the entire spectrum of
spatial and temporal scales, ranging from the molecular level (such as
bacterial growth, molecular and quantum dynamics) to the macroscopic
(e.g., seismology, ocean currents and plasma physics). Special
consideration will be given to novel tools that help extract features,
visualize remote data, run on distributed/heterogeneous systems, handle
format conversions, compress data, etc. Data analysis techniques such as
wavelet, cluster and statistical analysis, data assimilation (4D var),
together with any combination of wireless communication, high
performance scientific and community visualization, use of middleware,
and grid computing.
--
_______________________
Robin Tomlinson Pfister
Lead IMS Engineer, ESDIS Project
e-mail: robin.g.pfister at nasa.gov
Address: Mail Code 423
Org Code 586
NASA Goddard Space Flight Center
Greenbelt Md 20771
Phone: (301) 614-5171 Fax: (301) 614-5267
--
_______________________
Robin Tomlinson Pfister
Lead IMS Engineer, ESDIS Project
e-mail: robin.g.pfister at nasa.gov
Address: Mail Code 423
Org Code 586
NASA Goddard Space Flight Center
Greenbelt Md 20771
Phone: (301) 614-5171 Fax: (301) 614-5267
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