15,324 research outputs found
Collaboration in the Semantic Grid: a Basis for e-Learning
The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning
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Collaborative yet independent: Information practices in the physical sciences
In many ways, the physical sciences are at the forefront of using digital tools and methods to work with information and data. However, the fields and disciplines that make up the physical sciences are by no means uniform, and physical scientists find, use, and disseminate information in a variety of ways. This report examines information practices in the physical sciences across seven cases, and demonstrates the richly varied ways in which physical scientists work, collaborate, and share information and data.
This report details seven case studies in the physical sciences. For each case, qualitative interviews and focus groups were used to understand the domain. Quantitative data gathered from a survey of participants highlights different information strategies employed across the cases, and identifies important software used for research.
Finally, conclusions from across the cases are drawn, and recommendations are made. This report is the third in a series commissioned by the Research Information Network (RIN), each looking at information practices in a specific domain (life sciences, humanities, and physical sciences). The aim is to understand how researchers within a range of disciplines find and use information, and in particular how that has changed with the introduction of new technologies
Computational Particle Physics for Event Generators and Data Analysis
High-energy physics data analysis relies heavily on the comparison between
experimental and simulated data as stressed lately by the Higgs search at LHC
and the recent identification of a Higgs-like new boson. The first link in the
full simulation chain is the event generation both for background and for
expected signals. Nowadays event generators are based on the automatic
computation of matrix element or amplitude for each process of interest.
Moreover, recent analysis techniques based on the matrix element likelihood
method assign probabilities for every event to belong to any of a given set of
possible processes. This method originally used for the top mass measurement,
although computing intensive, has shown its power at LHC to extract the new
boson signal from the background.
Serving both needs, the automatic calculation of matrix element is therefore
more than ever of prime importance for particle physics. Initiated in the
eighties, the techniques have matured for the lowest order calculations
(tree-level), but become complex and CPU time consuming when higher order
calculations involving loop diagrams are necessary like for QCD processes at
LHC. New calculation techniques for next-to-leading order (NLO) have surfaced
making possible the generation of processes with many final state particles (up
to 6). If NLO calculations are in many cases under control, although not yet
fully automatic, even higher precision calculations involving processes at
2-loops or more remain a big challenge.
After a short introduction to particle physics and to the related theoretical
framework, we will review some of the computing techniques that have been
developed to make these calculations automatic. The main available packages and
some of the most important applications for simulation and data analysis, in
particular at LHC will also be summarized.Comment: 19 pages, 11 figures, Proceedings of CCP (Conference on Computational
Physics) Oct. 2012, Osaka (Japan) in IOP Journal of Physics: Conference
Serie
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