Encouraging collaboration through a new data management approach
Encouraging collaboration through a new data management approach
The ability to store large volumes of data is increasing faster than processing power. Some existing data management methods often result in data loss, inaccessibility or repetition of simulations. We propose a framework which promotes collaboration and simplifies data management. In particular we have demonstrated the proposed framework in the scenario
of handling large scale data generated from biomolecular simulations in a multiinstitutional global collaboration. The framework has extended the ability of the Python problem solving environment to manage data files and metadata associated with simulations. We provide a transparent and seamless environment for user submitted code to analyse and post-process data stored in the framework. Based on this scenario we have further enhanced and extended the framework
to deal with the more generic case of enabling any existing data file to be post processed from any .NET enabled programming language.
Johnston, Steven
6b903ec2-7bae-4a56-9c21-eea0a70bfa2b
August 2006
Johnston, Steven
6b903ec2-7bae-4a56-9c21-eea0a70bfa2b
Cox, Simon J.
0e62aaed-24ad-4a74-b996-f606e40e5c55
Fanghor, Hans
327e1141-7795-454e-bfe6-884a3b044093
Johnston, Steven
(2006)
Encouraging collaboration through a new data management approach.
University of Southampton, School of Engineering Sciences, Doctoral Thesis, 188pp.
Record type:
Thesis
(Doctoral)
Abstract
The ability to store large volumes of data is increasing faster than processing power. Some existing data management methods often result in data loss, inaccessibility or repetition of simulations. We propose a framework which promotes collaboration and simplifies data management. In particular we have demonstrated the proposed framework in the scenario
of handling large scale data generated from biomolecular simulations in a multiinstitutional global collaboration. The framework has extended the ability of the Python problem solving environment to manage data files and metadata associated with simulations. We provide a transparent and seamless environment for user submitted code to analyse and post-process data stored in the framework. Based on this scenario we have further enhanced and extended the framework
to deal with the more generic case of enabling any existing data file to be post processed from any .NET enabled programming language.
Text
StevenJamesJohnston-Thesis.pdf
- Accepted Manuscript
More information
Published date: August 2006
Organisations:
University of Southampton
Identifiers
Local EPrints ID: 65549
URI: http://eprints.soton.ac.uk/id/eprint/65549
PURE UUID: b4372149-d81d-4a87-bf81-6c58cd8c4d3e
Catalogue record
Date deposited: 19 Feb 2009
Last modified: 13 Mar 2024 17:45
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Contributors
Thesis advisor:
Hans Fanghor
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