Difference between revisions of "Emergence of e-Science"

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*Need for Usage of remote software<br>
*Need for Usage of remote software<br>
*Need for re-usable ICT component


*Large-scale parameter studies<br>
*Large-scale parameter studies<br>
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*[[Data-intensive Computing]]<br>
*[[Data-intensive Computing]]<br>


*[[Virtual Integration]]
*[[Virtual Integration]]<br>
<br>
 
*[[Parallel Computing]]<br>


==Inhibitors:==
==Inhibitors:==
- Extending the retirement age to another 10 years so people will have to work more
* Organizational Issues concerning authorization, and administration
* Lagacy Systems
* Productivity Gap


==Paradigms:==
==Paradigms:==
There has been enormous concern about the consequences of human population growth for the environment and for social and economic development. But this growth is likely to come to an end in the foreseeable future.
E-Science essentially means that many areas of science currently using computing resources as part of their research, will soon have the ability to utilize more powerful computing resources across grid. Geographically distributed scientists, in fields such as engineering, physics, earth science, bio-science, and chemistry, will have access to very large data sets and perform real time experiments on this data collaboratively. With the promotion of the collaborative development of large-scale multi-disciplinary applications, and the immersive visualization of large multi-dimensional data sets, it will ultimately lead to scientists tackling the 'big scientific questions' hitherto unexplorable. <br>


==Experts:==
==Experts:==
Research Councils UK<br>
Research Councils UK<br>
London e-Science Centre <br>


==Timing:==
==Timing:==
Improving on earlier methods of probabilistic forecasting, here we show that there is around an 85 per cent chance that the world's population will stop growing before the end of the century. There is a 60 per cent probability that the world's population will not exceed 10 billion people before 2100, and around a 15 per cent probability that the world's population at the end of the century will be lower than it is today. For different regions, the date and size of the peak population will vary considerably.
Emerging distributed collaborative scientific enterprises require desktop access to very large data collections, very large-scale computing resources, and high performance visualization.


==Web Resources:==
==Web Resources:==
http://www.vl-e.nl/frame_home.htm
http://www.vl-e.nl/frame_home.htm <br>
http://www.rcuk.ac.uk/
http://www.rcuk.ac.uk/<br>
 
http://www.lesc.ic.ac.uk/projects/index.html<br>
A list of almost all the English Institutions that research on e-Science:
http://www.wesc.ac.uk/links/index.html<br>
Background information and International projects: http://e-science.ox.ac.uk/info/ <br>
National e-Science Centre http://www.nesc.ac.uk/<br>


[http://scenariothinking.org/wiki/index.php/Technological_Driving_Forces >>back>>]
[http://scenariothinking.org/wiki/index.php/Technological_Driving_Forces >>back>>]

Latest revision as of 12:27, 17 March 2005

Description:

E-Science is a whole new concept just emerged.

In the future, e-Science will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. Typically, a feature of such collaborative scientific enterprises is that they will require access to very large data collections, very large scale computing resources and high performance visualisation back to the individual user scientists.

The Grid is the architecture proposed to bring all these issues together and make a reality of such a vision for e-Science. Ian Foster and Carl Kesselman, inventors of the Globus approach to the Grid define the Grid as an enabler for Virtual Organisations: ‘An infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources.’ As a result, e-Science can be deemed as the driving force for Grid's future development.

Enablers:

  • Technogical adavnces in GRID
  • Technogical advances in parallel programming
  • Increasing demand for large computational systems, data storage and specialized experimental facilities.
  • Collaborative engineering
  • Need for browsing of remote datasets
  • Need for Usage of remote software
  • Need for re-usable ICT component
  • Large-scale parameter studies

Inhibitors:

  • Organizational Issues concerning authorization, and administration
  • Lagacy Systems
  • Productivity Gap

Paradigms:

E-Science essentially means that many areas of science currently using computing resources as part of their research, will soon have the ability to utilize more powerful computing resources across grid. Geographically distributed scientists, in fields such as engineering, physics, earth science, bio-science, and chemistry, will have access to very large data sets and perform real time experiments on this data collaboratively. With the promotion of the collaborative development of large-scale multi-disciplinary applications, and the immersive visualization of large multi-dimensional data sets, it will ultimately lead to scientists tackling the 'big scientific questions' hitherto unexplorable.

Experts:

Research Councils UK
London e-Science Centre

Timing:

Emerging distributed collaborative scientific enterprises require desktop access to very large data collections, very large-scale computing resources, and high performance visualization.

Web Resources:

http://www.vl-e.nl/frame_home.htm
http://www.rcuk.ac.uk/
http://www.lesc.ic.ac.uk/projects/index.html
A list of almost all the English Institutions that research on e-Science: http://www.wesc.ac.uk/links/index.html
Background information and International projects: http://e-science.ox.ac.uk/info/
National e-Science Centre http://www.nesc.ac.uk/

>>back>>