GRID Computing - enabling the next generation of Solid Earth and Environmental Research in Australia  

Authors / CoAuthors

Wyborn, L.A.I. | Esterle, J.S.

Abstract

Earth comprises systems of enormous complexity that sustain all life and control the distribution of our mineral, energy and water resources. Increasingly earth scientists are now moving away from focusing on single domain research on understanding isolated parts of these intricate systems to adopting multidisciplinary, computationally intensive integrated methodologies to model and simulate the real world complexities of earth systems science. Simultaneously developments in information technology are increasing the capacity of computational systems to credibly simulate complex systems. Real world Solid Earth and Environmental Science data sets are extremely heterogenous, complex and large, and are currently in the order of terabytes (1012 bytes). However, the size and complexity of geoscience data sets are also exponentially increasing, as more powerful modern computing systems combine with enhanced engineering capacity to design and build automated instruments to collect more data and new data types. We are rapidly moving into an era when Earth Scientists will need to have the capacity to analyse petabyte (1015 bytes) databases if they are to realistically model and simulate complex earth processes. Although digital geoscientific data sets are becoming increasingly available over the Internet, current Internet technologies only allow for the downloading of data (if the connection is fast enough): integration, processing and analysis then has to take place locally. As data sets get larger and more complex, then large computational resources are required to effectively process these data. Such resources are increasingly only available to the major industry players, which in turn creates a strong bias against the Small to Middle Enterprises, as well as many University researchers. For those that do not have access to large-scale computing resources, analysis of these voluminous data sets has to be compromised by dividing the data set into smaller units, accepting sub-optimal solutions and/or introducing sub-optimal approximations. It is clear that if we are to begin grappling with accurate analysis of large-scale geoscientific data sets to enable sustainable management of our mineral, energy and water resources, then current computational infrastructures are no longer viable.

Product Type

nonGeographicDataset

eCat Id

60882

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Keywords

• External PublicationScientific Journal Paper

( Theme )

• geoscience

( Theme )

• geoscience databases

( Theme )

• information management

( Theme )

• resource management

Australian and New Zealand Standard Research Classification (ANZSRC)

• Earth Sciences

• Published_Internal

Publication Date

2003-01-01T00:00:00

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Australian Government Security ClassificationSystem    

Classification - unclassified

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Creative Commons Attribution 4.0 International Licence    

Access - restricted

Use - license

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Purpose

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unknown

Topic Category

geoscientificInformation

Series Information

106, 21-24

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Unknown

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