Managing large volumes of distributed scientific data

Steven Johnston, Hans Fangohr, Simon J. Cox Cox

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.We propose an implementation independent framework to promote collaboration and data management across a distributed environment. We discuss the framework features using a .NET Framework implementation and demonstrate the capabilities through a simple example.
Original languageEnglish
Title of host publicationComputational Science - ICCS 2008
Subtitle of host publicationLecture Notes in Computer Science
EditorsM. Bubak, G. D. van Albada, J. Dongarra, P. M. A. Sloot
Number of pages10
ISBN (Electronic)9783540693895
Publication statusPublished - 23 Jun 2008
EventInternational Conference on Computational Science - Krakow, Poland
Duration: 23 Jun 200825 Jun 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743


ConferenceInternational Conference on Computational Science
Abbreviated titleICCS 2008
Internet address


  • File Object Model
  • Data management
  • database


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