Geoscience Reference
In-Depth Information
analysis, and management. Conversely, contemporary data services need to be firmly
grounded in not only scientific and education drivers, and community needs, but are
also greatly influenced by the myriad technological and sociological trends.
The following sections describe the key drivers and trends that have transformed
data provision and access from centralized systems that were once based on proprietary
architectures to modern, distributed data services. In the process, the new generation
of data services has also reshaped their use in research and education in new and inno-
vate ways.
Science Driver
Numerous national and international reports underscore the importance of interdis-
ciplinary ERE. Among them are
Grand Challenges in Environmental Science
(NRC,
2001) and
Complex Environmental Systems: Synthesis for Earth, Life, and Society
in the 21st Century
(NSF, 2003). National Research Council (NRC) report points to
a growing recognition that “natural systems--ecosystems, oceans, drainage basins,
including agricultural systems, the atmosphere, and so on--are not divided along dis-
ciplinary lines.” Two of the grand challenges identified by the NRC, biogeochemical
cycles, and climate variability, depend heavily on integration of data from several
disciplines. Another excellent example is hydrologic forecasting, one of the four chal-
lenges prioritized as deserving immediate investment.
According to the former NSF director Rita Colwell (1998), “Interdisciplinary
connections are absolutely fundamental. They are synapses in this new capability to
look over and beyond the horizon. Interfaces of the sciences are where the excitement
will be the most intense...” For example, studies on societal impact of and emergency
management during hurricane-related fl998), involve integrating data from atmo-
spheric sciences, oceanography, hydrology, geology, geography, and social sciences
with databases in the social sciences.
The NSF decadal plan for Environmental Research and Education (ERE) also
echoes the need for improving our understanding of the natural and human processes
that govern quantity, quality, and availability of freshwater resources in the world.
While recent advances in remote sensing, combined with a new generation of coupled
models, are driving a new revolution in hydrometeorological predictions, future re-
search, and education in this area will require fi nding and integrating observational
and model data from the oceans, the atmosphere, the cryosphere, and the lithosphere,
crossing the traditional disciplinary boundaries.
Similar multidisciplinary needs are emerging to solve certain disaster/crisis manage-
ment problems. Two highly topical examples are fire-weather forecasting and
environmental modeling for homeland security. In homeland security, for instance,
there is a need to forecast the dispersal of hazardous radioactive, biological, and
chemical materials that may be released (accidentally or deliberately by terrorism)
into the atmosphere. For the latter scenario, detailed, four-dimensional information
on transport and dispersion of hazardous materials through the atmosphere, and their
deposition to the ground are needed at a resolution of individual community scales.
Moreover, this information needs to be linked in real-time to databases of population,
