Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data

Hieu T Nim; Falk Schreiber; Terence J Done; Sarah Elizabeth Boyd

doi:10.1109/BDVA.2015.7314297

Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data

Hieu T Nim, Falk Schreiber, Terence J Done, Sarah Elizabeth Boyd

Australian Regenerative Medicine Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

2 Citations (Scopus)

Abstract

The Great Barrier Reef is at critical risk of rapid decline, with mass coral bleaching following heatwave conditions constituting the most recent impact on the ecosystem. Here we describe an information-rich integrative visualisation suite of tools, tailored to ecologist users, for exploring a rich data set collected from the 2002 Great Barrier Reef heat stress event. Integration of data from multiple resources demonstrates how this visualisation is easily adaptable to any equivalent data, including data integration and visualisation from coral reef monitoring programs. The toolkit also makes such data accessible to any user for education, exploration and decisionmaking purposes.

Original language	English
Title of host publication	2015 Big Data Visual Analytics (BDVA)
Editors	Ulrich Engelke, Julian Heinrich, Tomasz Bednarz, Karsten Klein, Quang Vinh Nguyen
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-7
Number of pages	7
Volume	1
DOIs	https://doi.org/10.1109/BDVA.2015.7314297
Publication status	Published - 2015
Event	International Symposium on Big Data Visual Analytics (BDVA 2015) - Hobart, Australia Duration: 22 Sep 2015 → 25 Sep 2015 http://www.bdva.net/2015/

Conference

Conference	International Symposium on Big Data Visual Analytics (BDVA 2015)
Abbreviated title	BDVA 2015
Country	Australia
City	Hobart
Period	22/09/15 → 25/09/15
Internet address	http://www.bdva.net/2015/

Keywords

big data analytics
human-readable visualisation
geolocational data
species composition
ecological traits
coral bleaching

Cite this

Nim, H. T., Schreiber, F., Done, T. J., & Boyd, S. E. (2015). Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data. In U. Engelke, J. Heinrich, T. Bednarz, K. Klein, & Q. V. Nguyen (Eds.), 2015 Big Data Visual Analytics (BDVA) (Vol. 1, pp. 1-7). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BDVA.2015.7314297

Nim, Hieu T ; Schreiber, Falk ; Done, Terence J ; Boyd, Sarah Elizabeth. / Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data. 2015 Big Data Visual Analytics (BDVA). editor / Ulrich Engelke ; Julian Heinrich ; Tomasz Bednarz ; Karsten Klein ; Quang Vinh Nguyen. Vol. 1 Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2015. pp. 1-7

@inproceedings{79c9e741f0bd466ba97ddf8327a8c7a5,

title = "Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data",

abstract = "The Great Barrier Reef is at critical risk of rapid decline, with mass coral bleaching following heatwave conditions constituting the most recent impact on the ecosystem. Here we describe an information-rich integrative visualisation suite of tools, tailored to ecologist users, for exploring a rich data set collected from the 2002 Great Barrier Reef heat stress event. Integration of data from multiple resources demonstrates how this visualisation is easily adaptable to any equivalent data, including data integration and visualisation from coral reef monitoring programs. The toolkit also makes such data accessible to any user for education, exploration and decisionmaking purposes.",

keywords = "big data analytics, human-readable visualisation, geolocational data, species composition, ecological traits, coral bleaching",

author = "Nim, {Hieu T} and Falk Schreiber and Done, {Terence J} and Boyd, {Sarah Elizabeth}",

year = "2015",

doi = "10.1109/BDVA.2015.7314297",

language = "English",

volume = "1",

pages = "1--7",

editor = "Ulrich Engelke and Julian Heinrich and Tomasz Bednarz and Karsten Klein and Nguyen, {Quang Vinh}",

booktitle = "2015 Big Data Visual Analytics (BDVA)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

}

Nim, HT, Schreiber, F, Done, TJ & Boyd, SE 2015, Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data. in U Engelke, J Heinrich, T Bednarz, K Klein & QV Nguyen (eds), 2015 Big Data Visual Analytics (BDVA). vol. 1, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 1-7, International Symposium on Big Data Visual Analytics (BDVA 2015), Hobart, Australia, 22/09/15. https://doi.org/10.1109/BDVA.2015.7314297

Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data. / Nim, Hieu T; Schreiber, Falk; Done, Terence J; Boyd, Sarah Elizabeth.

2015 Big Data Visual Analytics (BDVA). ed. / Ulrich Engelke; Julian Heinrich; Tomasz Bednarz; Karsten Klein; Quang Vinh Nguyen. Vol. 1 Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2015. p. 1-7.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data

AU - Nim, Hieu T

AU - Schreiber, Falk

AU - Done, Terence J

AU - Boyd, Sarah Elizabeth

PY - 2015

Y1 - 2015

N2 - The Great Barrier Reef is at critical risk of rapid decline, with mass coral bleaching following heatwave conditions constituting the most recent impact on the ecosystem. Here we describe an information-rich integrative visualisation suite of tools, tailored to ecologist users, for exploring a rich data set collected from the 2002 Great Barrier Reef heat stress event. Integration of data from multiple resources demonstrates how this visualisation is easily adaptable to any equivalent data, including data integration and visualisation from coral reef monitoring programs. The toolkit also makes such data accessible to any user for education, exploration and decisionmaking purposes.

AB - The Great Barrier Reef is at critical risk of rapid decline, with mass coral bleaching following heatwave conditions constituting the most recent impact on the ecosystem. Here we describe an information-rich integrative visualisation suite of tools, tailored to ecologist users, for exploring a rich data set collected from the 2002 Great Barrier Reef heat stress event. Integration of data from multiple resources demonstrates how this visualisation is easily adaptable to any equivalent data, including data integration and visualisation from coral reef monitoring programs. The toolkit also makes such data accessible to any user for education, exploration and decisionmaking purposes.

KW - big data analytics

KW - human-readable visualisation

KW - geolocational data

KW - species composition

KW - ecological traits

KW - coral bleaching

UR - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7314297

U2 - 10.1109/BDVA.2015.7314297

DO - 10.1109/BDVA.2015.7314297

M3 - Conference Paper

VL - 1

SP - 1

EP - 7

BT - 2015 Big Data Visual Analytics (BDVA)

A2 - Engelke, Ulrich

A2 - Heinrich, Julian

A2 - Bednarz, Tomasz

A2 - Klein, Karsten

A2 - Nguyen, Quang Vinh

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

ER -

Nim HT, Schreiber F, Done TJ, Boyd SE. Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data. In Engelke U, Heinrich J, Bednarz T, Klein K, Nguyen QV, editors, 2015 Big Data Visual Analytics (BDVA). Vol. 1. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2015. p. 1-7 https://doi.org/10.1109/BDVA.2015.7314297

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10.1109/BDVA.2015.7314297

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Interactive geolocational and coral compositional visualisation of Great Barrier Reef heat stress data

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Keywords

Cite this

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