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2 - Introduction to IT concepts and challenges

from Introduction

Published online by Cambridge University Press:  25 October 2011

Chaitanya Baru
Affiliation:
University of California-San Diego
G. Randy Keller
Affiliation:
University of Oklahoma
Chaitanya Baru
Affiliation:
University of California, San Diego
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Summary

Scientific applications have been at the forefront of driving computer and information technology since the early days: from the development of early computers for numerical computing, to the introduction in the USA of the NSFNET (which helped launch the Internet), and the subsequent invention of the World Wide Web. The geosciences, in particular, have been a long-standing user of such technologies, given the importance of applications related to weather, natural resources, natural hazards, and environmental monitoring. Scientific computing was focused initially on the need for fast computers to perform larger numbers of complex numerical calculations. The concerns more recently have turned towards the ability to manage the very large amounts of data that are being generated by a wide range of sensors and instruments, sophisticated observing systems, and large-scale simulations on large computer systems. Data rates of terabytes per day and petabytes per year are not uncommon (1 petabyte = terabytes) (Hey et al., 2009, p. 9). Yet, computer science and information technology solutions must deal not only with the size and scale of data, but also the inherent richness and complexity of scientific data – especially when data are combined across multiple projects, institutions, and even multiple science disciplines and subdisciplines. The need to understand complex, interdependent, natural as well as anthropogenic phenomena has made science a team sport, requiring collaborations among multidisciplinary teams of scientists to process, analyze, and integrate extremely heterogeneous data.

Type
Chapter
Information
Geoinformatics
Cyberinfrastructure for the Solid Earth Sciences
, pp. 10 - 18
Publisher: Cambridge University Press
Print publication year: 2011

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References

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,GeoSciML Resource Repository (2010), www.geosciml.org.
,GSA Geoinformatics Division Bylaws (2006), p. 1, March, www.geoexpertsintl.com/geoinformatics/pdf/geoinfoBylaws.pdf.
Hey, T., Tansley, S., and Tolle, K. (2009). The Fourth Paradigm: Data-Intensive Scientific Discovery. Redmond, WA: Microsoft Research.Google Scholar
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,NSF Cyberinfrastructure Vision for 21st Century Discovery, National Science Foundation report (2007), www.nsf.gov/pubs/2007/nsf0728/index.jsp.
,NSF EAR/IF (2010), NSF Earth Sciences Division: Instrumentation and Facilities, www.nsf.gov/pubs/2005/nsf05587/nsf05587.htm
,PaleoDB: The Paleobiology Database (2010), http://paleodb.org.
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Youn, C., Kaiser, T., Santini, C., and Seber, D. (2005). Design and implementation of services for a synthetic seismogram calculation tool on the Grid. In Proceedings of the 5th International Conference (ICCS 2005), Atlanta, GA, USA, May 22–25, 2005. Part I, LNCS 3514. Berlin: Springer, p. 469.Google Scholar

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