Data integration and application of marine environmental monitor-ing based on large data
Abstract
to face the integration of multiple-source heterogeneous mass data, Traditional integration methods and techniques cannot implement, until large data technology out of is now possible. Application of large data technology for multi-source heterogeneous marine Environment Monitoring data integration, Benefits marine Environment monitoring to share, Avoid islands of information, Simultaneous analysis of data, Mining provides the required data. The article focuses on the based on large data and data virtualization platform Technology, Reference ODM 2 Information model and MMI ORR Ontology semantic Framework for multiple source Heterogeneous marine environmental monitoring data integration issue , And on the basis of data integration, explores multi-source heterogeneous data queries, Consolidated Show implementation of the application . This research is helpful to solve the problem of massive marine environment monitoring data management problems , Meeting marine environment Research workers author large data requirements , Implementing data-driven decisions ,,Promote marine environment management level .
Keywords
Full Text:
PDFReferences
Szaby S, Gray J. Science in a exponenl^ial Word [j]. Nature, 2006,440:23-24.
H Gilbert M illerpelermork, nob Lis. From Data Id decisions^: A Value Chan lor Big Data [J]. IT prolessibna!, 2013,15 0 : ) 57-58.
Andrew bru^t:gartner releases 2013 Data Warehouse Magic Quadrant Eb/ol]. 2013-05 HTTP^^WW.ZDN Eticom/arl^icle/garlner-releases-2013-data-warehouse-m agic-quadrant/.
X n Luna Dong, Divesh S^ivastava. B g Data integrat^ion [c]//ieee 29th In^mat^idnalcon^renceon Data Engineer-ing (ICDE), 2013: /b12>1245-1248.
April Reeve. Managiig data in MOTDN data Integratdn best Practice technques and Technodges M]. San Francsco: M organ kaulm Ann Publishers, 2013:142-156.
J Dean, S ghemawat Data processing on Large clusters[c]//osdi.
cuttingd. Scalabecomputingwith Mapreduce[c]//prdcofo ' Reilly Open sourceconventdn,poland. th
overvew.the Open Service Network for Marine environmental Data Netmar) eb/ B20>0 l].2009-06 http://hetmar.nersc.nD/
jeffde labeaujardfere. THENOAA ioos Data integratdn framework:initial implementatdn [R]. IEEE publsh-ers,2008:1-8.
NOAA announcesrfi tounleash powerof ' Bigdata ' eb/ol]. [2014-02-24]http^^ww.ndaanews.ndaa.gdv/^^ ^es2014/20140224 _bigdata.htm l,.
Comments of the informatdn technodgy Industry council* Response to the big Data Request IDr Informatdn Eb/ol]. 2014-03-27 http//www.itic.o_otasset/bcae1b74-eb8e-4101-a02d-7e8aa8bda1idf.pdf.
Miaomiao, B n Zhou,zhun Zhou. The Interoperatdn Framework ofocean observatdn datausiigspatial informatdn service[c]//2nd intematdnal Conference on
Comp Uterscence and Network technodgy, Changchun.
John graybeal Anthony W isenor, Carlosrueda. Semanticmediation Ofvocabulariesforocean observingsystems [J1 computers& geosciences*.
Jing X iong, Jpeng W ang, Feng Gao. ontology-based Marine Ecology Knowledge Management [J]. Informatics and Managementscience II, 2013,205465-471.
Dhruba Borthakur, Jonathan Gray, etal. Apache H adoop Goes realtim e at Facebook [c]//proceedings for the ACM sigmod International Conference on Managementof Data. New YORK:ACM Publishers, 2011:1071-1080.
Shen Letter , Wang Wei . Is based on the tree-lb Large Data real-time analysis of [J]. Computer Science , 2013,406): 192-196.
Robert Eve. B Igdalameelsvirtualizationeb/ol]. 2011-05-17 http://roberteve1.sys-con.com/hode/1835758.
Overview. jbossdatavirtualizationeb/ol].2014http^wwlossorg/productsdatavirl/overview/.
aboutteiid Eb/ol]. 2014 http//feiid. lost ossorg/about/.
Benjamin T Hazen, Christopher A Boone, etal* data Quality for Data science, predictive Analytics, and big Dala I n Supply Chain Management:an Introduction to the Problem and suggestions for the and applications [J]. International Journal of Production Economics editorial Board, 2014,154:72-80.
Pope , Wu Feng . challenges to data quality in a large data age [J]. Journal of Xian Jiaotong University : Social Science edition . 2013,335): 38-43.
Huang Dongmei , Chen Kuo , , and so on . selection algorithm for large ocean data quality inspection scheme based on block nesting cycle [J]. Computer Engineering and Science ,2013.10,3510 51-57.
Vision for the fulure of the data integration market-impact Eb/ol]. https://Www.youtube.com/Watch? v=yziu4yv_bue.2011-06-23.
van Derlansr F. Data virtualization forbusiiess INTELLIGENCESYSTEMSM]. Waltham,ma:morgan Kauimann Publishers, 20128-9
Noel Yuhanna, Mike G ilpiithe. Forrester wave:data Virtualization, Q1 Eb/ol]. 2012-01-05 http//72.41.218.229/adm in/uploads/15723400631342780586.pdf.
Tom Plunkett Brian MacDonald, Etal. Oracle Big Data Handbook M]. Osbome/mcgraw-hill, 2013:1-12.
informatica powercenter Big Dala Edition eb/ol]. 2014-12/2015-11-09 http/ Www.predictiveanalyticslDday.com/iiformatica -powercenter-big-dala-ed ition/
Lum fy fealures n action eb/ol]. 2013-112-13 https://www.youtube.com/watchv=CAR8mon7EZs (
The death of trad itional Dala irtegration eb/ol]. 2015-01-28 Httpy/campaign&snaplogic.com/death-of-trad Itional-ntegration.hlml.
Sam na R abidi, Syed SR Abidi, Mei Kwan, etal. An Ontology Framework for modeling Ocean Data and E-science semantic Web services[j]. Intemational Journal of Advanced Computer Science, 2012,2 8) 280-286.
Yannis Tzitzikas, Carlo Allocca, Chryssoula Bekiari, etal. Heterogeneous and distributed in1formatior about Marne
DOI: http://dx.doi.org/10.18686/me.v2i1.1186
Refbacks
- There are currently no refbacks.
