A computational pipeline for the IUCN risk assessment for meso-American reef ecosystem

Nguyen, Hoang Anh, Bland, Lucie, Roberts, Tristan, Guru, Siddeswara, Dinh, Minh and Abramson, David (2017). A computational pipeline for the IUCN risk assessment for meso-American reef ecosystem. In: 2017 IEEE 13Th International Conference On E-Science (E-Science). 13th Annual IEEE International Conference on e-Science (e-Science), Auckland, New Zealand, (286-294). 24 - 27 October 2017. doi:10.1109/eScience.2017.42


Author Nguyen, Hoang Anh
Bland, Lucie
Roberts, Tristan
Guru, Siddeswara
Dinh, Minh
Abramson, David
Title of paper A computational pipeline for the IUCN risk assessment for meso-American reef ecosystem
Conference name 13th Annual IEEE International Conference on e-Science (e-Science)
Conference location Auckland, New Zealand
Conference dates 24 - 27 October 2017
Convener IEEE
Proceedings title 2017 IEEE 13Th International Conference On E-Science (E-Science)   Check publisher's open access policy
Journal name 2017 Ieee 13Th International Conference On E-Science (E-Science)   Check publisher's open access policy
Place of Publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Publication Year 2017
Year available 2017
Sub-type Fully published paper
DOI 10.1109/eScience.2017.42
Open Access Status Not yet assessed
ISBN 9781538626863
9781538626870
ISSN 2325-372X
Start page 286
End page 294
Total pages 9
Language eng
Abstract/Summary Coral reefs are of global economic and biological significance but are subject to increasing threats. As a result, it is essential to understand the risk of coral reef ecosystem collapse and to develop assessment process for those ecosystems. The International Union for Conservation of Nature (IUCN) Red List of Ecosystem (RLE) is a framework to assess the vulnerability of an ecosystem. Importantly, the assessment processes need to be repeatable as new monitoring data arises. The repeatability will also enhance transparency. In this paper, we discuss the evolution of a computational pipeline for risk assessment of the Meso-American reef ecosystem, a diverse reef ecosystem located in the Caribbean, with the focus on improving the execution time starting from sequential and parallel implementation and finally using Apache Spark. The final form of the pipeline is a scientific workflow to improve its repeatability and reproducibility.
Keyword Apache spark
Ecosystem risk assessment
Many task computing
Scientific workflow
Q-Index Code E1
Q-Index Status Provisional Code
Grant ID LP 130100435
Institutional Status UQ

Document type: Conference Paper
Sub-type: Fully published paper
Collections: HERDC Pre-Audit
School of Information Technology and Electrical Engineering Publications
 
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