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Shuo, Liang, Holmes, Violeta, Antoniou, Grigoris and Higgins, Joshua (2015) iCurate: A Research Data Management System. In: Multi-disciplinary Trends in Artificial Intelligence. Lecture Notes in Computer Science (9426). Springer, Fuzhou, China,, pp. 39-47. ISBN ISBN 978-3-319-26181-2
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Abstract
Scientific research activities generate a large amount of data, which varies in format, volume, structure and ownership. Although there are revision control systems and databases developed for data archiving, the traditional data management methods are not suitable for High Performance Computing (HPC) systems. The files in such systems do not have semantic annotations and cannot be archived and managed for public dissemination.
We have proposed and developed a Research Data Management (RDM)system, iCurate', which provides easy-to-use RDM facilities with semantic annotations. The system incorporates Metadata Retrieval, Departmental Archiving, Workflow Management System, Meta data Validation and Self Inferencing. The `i' emphasises the user-oriented design. iCurate will support researchers by annotating their data in a clearer and machine readable way from its production to publication for the future reuse
| Item Type: | Book Chapter |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Schools: | School of Computing and Engineering School of Computing and Engineering > High-Performance Intelligent Computing > High Performance Computing Research Group |
| Depositing User: | Violeta Holmes |
| Date Deposited: | 28 Mar 2017 15:51 |
| Last Modified: | 28 Aug 2021 16:07 |
| URI: | https://eprints.hud.ac.uk/id/eprint/31633 |
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iCurate: A Research Data Management System. (deposited 02 Jun 2016 14:38)
- iCurate: A Research Data Management System. (deposited 28 Mar 2017 15:51) [Currently Displayed]
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