Grid Computing 2003
DOI: 10.1002/0470867167.ch36
|View full text |Cite
|
Sign up to set email alerts
|

The Data Deluge: An e‐Science Perspective

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
222
0
8

Year Published

2003
2003
2012
2012

Publication Types

Select...
7
2
1

Relationship

0
10

Authors

Journals

citations
Cited by 365 publications
(230 citation statements)
references
References 11 publications
0
222
0
8
Order By: Relevance
“…35 As Hey and Trefethen put it, it is evident that e-science data generated from sensors, satellites, high-performance computer simulations, high-throughput devices, scientific images and so on will soon dwarf all of the scientific data collected in the whole history of scientific exploration. 36 The US National Research Council suggests that:…”
Section: Information Search and Accessmentioning
confidence: 99%
“…35 As Hey and Trefethen put it, it is evident that e-science data generated from sensors, satellites, high-performance computer simulations, high-throughput devices, scientific images and so on will soon dwarf all of the scientific data collected in the whole history of scientific exploration. 36 The US National Research Council suggests that:…”
Section: Information Search and Accessmentioning
confidence: 99%
“…the massive (and growing) amounts of digital information now being generated, combined with a proliferation of format types. The Web is but one exemplar of this, another being the 'data deluge' now apparent in many scientific disciplines, whereby vast amounts of data are being generated by high-throughput instruments or streamed from sensors or satellites (Hey & Trefethen, 2003;Szalay & Gray, 2006 (Gomes & Silva, 2005). By contrast, the first domain harvest of the Australian Web in 2005 took six weeks and captured 185 million documents or 6.69 Terabytes of data (Koerbin, 2005).…”
Section: Other Challengesmentioning
confidence: 99%
“…17 How to manage the data deluge from 'e-science' -large-scale, international projects in bioinformatics, proteomics, and grid computing -and how to get from raw data to authoritative, peerreviewed knowledge is a crucial issue. 18 From the CrossRef point of view the major issues in these areas are interlinking all this data with the peer-reviewed literature and applying the same model of identification with DOIs and standardized metadata to databases and other types of content so that they can be persistently cited and linked to. CrossRef is working with the Protein Data Bank and other database producers on these issues.…”
Section: Trends In Scholarly Publishingmentioning
confidence: 99%