Multi-Disciplinary Approaches To Intelligently Sharing Large-Volumes Of 
Real-Time Sensor Data During Natural Disasters

Middleton, S. E.; Sabeur, Z. A.; Löwe, Peter; Hammitzsch, Martin; Tavakoli, S.; Poslad, S.

doi:10.2481/dsj.WDS-018

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Multi-Disciplinary Approaches To Intelligently Sharing Large-Volumes Of Real-Time Sensor Data During Natural Disasters

Middleton, S. E., Sabeur, Z. A., Löwe, P., Hammitzsch, M., Tavakoli, S., Poslad, S. (2013): Multi-Disciplinary Approaches To Intelligently Sharing Large-Volumes Of Real-Time Sensor Data During Natural Disasters. - Data Science Journal, 12, WDS109-WDS113.
https://doi.org/10.2481/dsj.WDS-018

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Middleton, S. E.¹, Author
Sabeur, Z. A.¹, Author
Löwe, Peter², Author
Hammitzsch, Martin², Author
Tavakoli, S.¹, Author
Poslad, S.¹, Author

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1External Organizations, ou_persistent22
2CeGIT Centre for GeoInformation Technology, Geoengineering Centres, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_44023

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Dates: Finally published : 2013

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Identifiers: eDoc: 19588
GFZPOF: PT3 Natural Hazards: Assessment and Risk Mitigation
DOI: 10.2481/dsj.WDS-018

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Title: Data Science Journal

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Pages: - Volume / Issue: 12 Sequence Number: - Start / End Page: WDS109 - WDS113 Identifier: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals2_102