ICurate: A Research Data Management System

Shuo Liang, Violeta Holmes, Grigoris Antoniou, Joshua Higgins

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

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationMulti-disciplinary Trends in Artificial Intelligence
Subtitle of host publication9th International Workshop, MIWAI 2015, Proceedings
EditorsAntonis Bikakis, Xianghan Zheng
PublisherSpringer Verlag
Pages39-47
Number of pages9
ISBN (Electronic)9783319261812
ISBN (Print)9783319261805
DOIs
Publication statusPublished - 29 Nov 2015
Event9th International Workshop on Multi-Disciplinary Trends in Artificial Intelligence - Fuzhou, China
Duration: 13 Nov 201515 Nov 2015
Conference number: 9
http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=43492&copyownerid=31599 (Link to Conference Information)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9426
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference9th International Workshop on Multi-Disciplinary Trends in Artificial Intelligence
Abbreviated titleMIWAI 2015
CountryChina
CityFuzhou
Period13/11/1515/11/15
Internet address

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Cite this

Liang, S., Holmes, V., Antoniou, G., & Higgins, J. (2015). ICurate: A Research Data Management System. In A. Bikakis, & X. Zheng (Eds.), Multi-disciplinary Trends in Artificial Intelligence: 9th International Workshop, MIWAI 2015, Proceedings (pp. 39-47). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9426). Springer Verlag. https://doi.org/10.1007/978-3-319-26181-2_4