Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework
Identifieur interne : 000118 ( Main/Exploration ); précédent : 000117; suivant : 000119Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework
Auteurs : Zhenlong Li [États-Unis] ; Chaowei Yang [États-Unis] ; Baoxuan Jin [États-Unis, République populaire de Chine] ; Manzhu Yu [États-Unis] ; Kai Liu [États-Unis] ; Min Sun [États-Unis] ; Matthew Zhan [États-Unis]Source :
- PLoS ONE [ 1932-6203 ] ; 2015.
Abstract
Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.
Url:
DOI: 10.1371/journal.pone.0116781
PubMed: 25742012
PubMed Central: 4351198
Affiliations:
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uniqKey="Yu M" first="Manzhu" last="Yu">Manzhu Yu</name><affiliation wicri:level="2"><nlm:aff id="aff001"><addr-line>NSF Spatiotemporal Innovation Center, George Mason University, Fairfax, VA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>NSF Spatiotemporal Innovation Center, George Mason University, Fairfax, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author><author><name sortKey="Liu, Kai" sort="Liu, Kai" uniqKey="Liu K" first="Kai" last="Liu">Kai Liu</name><affiliation wicri:level="2"><nlm:aff id="aff001"><addr-line>NSF Spatiotemporal Innovation Center, George Mason University, Fairfax, VA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>NSF Spatiotemporal Innovation Center, George Mason University, Fairfax, VA</wicri:regionArea><placeName><region 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Mason University, Fairfax, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation><affiliation wicri:level="2"><nlm:aff id="aff003"><addr-line>Department of Computer Science, University of Texas—Austin, Austin, Texas, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Computer Science, University of Texas—Austin, Austin, Texas</wicri:regionArea><placeName><region type="state">Texas</region></placeName></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Groot, R" uniqKey="Groot R">R Groot</name></author><author><name sortKey="Mclaughlin, Jd" uniqKey="Mclaughlin J">JD McLaughlin</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Yang, C" uniqKey="Yang C">C Yang</name></author><author><name sortKey="Li, W" uniqKey="Li W">W Li</name></author><author><name sortKey="Xie, J" uniqKey="Xie J">J Xie</name></author><author><name sortKey="Zhou, B" uniqKey="Zhou B">B Zhou</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yang, C" uniqKey="Yang C">C Yang</name></author><author><name sortKey="Goodchild, M" uniqKey="Goodchild M">M 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Guo</name></author><author><name sortKey="Gautam, N" uniqKey="Gautam N">N Gautam</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Mattmann, Ca" uniqKey="Mattmann C">CA Mattmann</name></author><author><name sortKey="Crichton, Dj" uniqKey="Crichton D">DJ Crichton</name></author><author><name sortKey="Hart, Af" uniqKey="Hart A">AF Hart</name></author><author><name sortKey="Goodale, C" uniqKey="Goodale C">C Goodale</name></author><author><name sortKey="Hughes, Js" uniqKey="Hughes J">JS Hughes</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Williams, Dn" uniqKey="Williams D">DN Williams</name></author><author><name sortKey="Drach, R" uniqKey="Drach R">R Drach</name></author><author><name sortKey="Ananthakrishnan, R" uniqKey="Ananthakrishnan R">R Ananthakrishnan</name></author><author><name sortKey="Foster, I" uniqKey="Foster I">I Foster</name></author><author><name sortKey="Fraser, D" uniqKey="Fraser D">D Fraser</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Huang, Q" uniqKey="Huang Q">Q Huang</name></author><author><name sortKey="Yang, C" uniqKey="Yang C">C Yang</name></author><author><name sortKey="Liu, K" uniqKey="Liu K">K Liu</name></author><author><name sortKey="Xia, J" uniqKey="Xia J">J Xia</name></author><author><name sortKey="Xu, C" uniqKey="Xu C">C Xu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yue, P" uniqKey="Yue P">P Yue</name></author><author><name sortKey="Di, L" uniqKey="Di L">L Di</name></author><author><name sortKey="Yang, W" uniqKey="Yang W">W Yang</name></author><author><name sortKey="Yu, G" uniqKey="Yu G">G Yu</name></author><author><name sortKey="Zhao, P" uniqKey="Zhao P">P Zhao</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Li, Z" uniqKey="Li Z">Z Li</name></author><author><name sortKey="Yang, C" uniqKey="Yang C">C Yang</name></author><author><name sortKey="Wu, H" uniqKey="Wu H">H Wu</name></author><author><name sortKey="Li, W" uniqKey="Li W">W Li</name></author><author><name sortKey="Miao, L" uniqKey="Miao L">L Miao</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>République populaire de Chine</li><li>États-Unis</li></country><region><li>Texas</li><li>Virginie</li></region></list><tree><country name="États-Unis"><region name="Virginie"><name sortKey="Li, Zhenlong" sort="Li, Zhenlong" uniqKey="Li Z" first="Zhenlong" last="Li">Zhenlong Li</name></region><name sortKey="Jin, Baoxuan" sort="Jin, Baoxuan" uniqKey="Jin B" first="Baoxuan" last="Jin">Baoxuan Jin</name><name sortKey="Liu, Kai" sort="Liu, Kai" uniqKey="Liu K" first="Kai" last="Liu">Kai Liu</name><name sortKey="Sun, Min" sort="Sun, Min" uniqKey="Sun M" first="Min" last="Sun">Min Sun</name><name sortKey="Yang, Chaowei" sort="Yang, Chaowei" uniqKey="Yang C" first="Chaowei" last="Yang">Chaowei Yang</name><name sortKey="Yu, Manzhu" sort="Yu, Manzhu" uniqKey="Yu M" first="Manzhu" last="Yu">Manzhu Yu</name><name sortKey="Zhan, Matthew" sort="Zhan, Matthew" uniqKey="Zhan M" first="Matthew" last="Zhan">Matthew Zhan</name><name sortKey="Zhan, Matthew" sort="Zhan, Matthew" uniqKey="Zhan M" first="Matthew" last="Zhan">Matthew Zhan</name></country><country name="République populaire de Chine"><noRegion><name sortKey="Jin, Baoxuan" sort="Jin, Baoxuan" uniqKey="Jin B" first="Baoxuan" last="Jin">Baoxuan Jin</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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