Experiments in applying advanced data mining and integration to hydro-meteorological scenarios

We present the results of applying advanced data integration and data mining (DMI) technology, developed in the FP7 project ADMIRE, to a set of hydro-meteorological pilot scenarios. The DMI technology includes a data processing architecture and its implementation by a set of tools, and a new DMI pro...

Full description

Saved in:
Bibliographic Details
Main Authors: Hluchy, L., Habala, O., Krammer, P., Seleng, M., Tran, V.
Format: Conference Proceeding
Language:English
Subjects:
Data mining
Data models
Predictive models
Radar imaging
Reservoirs
Temperature measurement
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 284
container_issue
container_start_page 279
container_title
container_volume
creator Hluchy, L.
Habala, O.
Krammer, P.
Seleng, M.
Tran, V.
description We present the results of applying advanced data integration and data mining (DMI) technology, developed in the FP7 project ADMIRE, to a set of hydro-meteorological pilot scenarios. The DMI technology includes a data processing architecture and its implementation by a set of tools, and a new DMI process definition language called DISPEL. It is based on the popular OGSA-DAI framework. The pilot scenarios were defined by hydrological and meteorological experts and their aim is to try predict hydro-meteorological processes in cases, where standard physical models for the chosen geographical domain are not present, or give unsatisfactory results. The obtained results show that the application of ADMIRE DMI technology is beneficient to the domain experts.
doi_str_mv 10.1109/ICSDM.2011.5969047
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5969047</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5969047</ieee_id><sourcerecordid>5969047</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-e970f4176c28e689bdaf2c7fd955de1a0ca4af6075ecff58d3bd2b63a6e993e83</originalsourceid><addsrcrecordid>eNpFUFFLwzAYjIigzv0Bfckf6EzSJG0eZc45mPjgnh1fky810iWlDWL_vUMH3stxx3FwR8gtZwvOmbnfLN8eXxaCcb5QRhsmqzNyzaWQsi4Vl-f_QohLMh_HT3aE1kaZ-oq8r757HMIBYx5piBT6vptCbCm4L4gWHXWQgR5C_DWjO4YytgPkkCLNiX5MbkjFATOmIXWpDRY6OlqMMIQ03pALD92I8xPPyO5ptVs-F9vX9Wb5sC2CYblAUzEveaWtqFHXpnHgha28M0o55MAsSPCaVQqt96p2ZeNEo0vQaEyJdTkjd3-1ARH3_XEPDNP-dEf5A9_VVv0</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Experiments in applying advanced data mining and integration to hydro-meteorological scenarios</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Hluchy, L. ; Habala, O. ; Krammer, P. ; Seleng, M. ; Tran, V.</creator><creatorcontrib>Hluchy, L. ; Habala, O. ; Krammer, P. ; Seleng, M. ; Tran, V.</creatorcontrib><description>We present the results of applying advanced data integration and data mining (DMI) technology, developed in the FP7 project ADMIRE, to a set of hydro-meteorological pilot scenarios. The DMI technology includes a data processing architecture and its implementation by a set of tools, and a new DMI process definition language called DISPEL. It is based on the popular OGSA-DAI framework. The pilot scenarios were defined by hydrological and meteorological experts and their aim is to try predict hydro-meteorological processes in cases, where standard physical models for the chosen geographical domain are not present, or give unsatisfactory results. The obtained results show that the application of ADMIRE DMI technology is beneficient to the domain experts.</description><identifier>ISBN: 1424483522</identifier><identifier>ISBN: 9781424483525</identifier><identifier>EISBN: 1424483514</identifier><identifier>EISBN: 1424483506</identifier><identifier>EISBN: 9781424483501</identifier><identifier>EISBN: 9781424483518</identifier><identifier>DOI: 10.1109/ICSDM.2011.5969047</identifier><language>eng</language><publisher>IEEE</publisher><subject>Data mining ; Data models ; Predictive models ; Radar imaging ; Reservoirs ; Temperature measurement</subject><ispartof>Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, 2011, p.279-284</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5969047$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5969047$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hluchy, L.</creatorcontrib><creatorcontrib>Habala, O.</creatorcontrib><creatorcontrib>Krammer, P.</creatorcontrib><creatorcontrib>Seleng, M.</creatorcontrib><creatorcontrib>Tran, V.</creatorcontrib><title>Experiments in applying advanced data mining and integration to hydro-meteorological scenarios</title><title>Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services</title><addtitle>ICSDM</addtitle><description>We present the results of applying advanced data integration and data mining (DMI) technology, developed in the FP7 project ADMIRE, to a set of hydro-meteorological pilot scenarios. The DMI technology includes a data processing architecture and its implementation by a set of tools, and a new DMI process definition language called DISPEL. It is based on the popular OGSA-DAI framework. The pilot scenarios were defined by hydrological and meteorological experts and their aim is to try predict hydro-meteorological processes in cases, where standard physical models for the chosen geographical domain are not present, or give unsatisfactory results. The obtained results show that the application of ADMIRE DMI technology is beneficient to the domain experts.</description><subject>Data mining</subject><subject>Data models</subject><subject>Predictive models</subject><subject>Radar imaging</subject><subject>Reservoirs</subject><subject>Temperature measurement</subject><isbn>1424483522</isbn><isbn>9781424483525</isbn><isbn>1424483514</isbn><isbn>1424483506</isbn><isbn>9781424483501</isbn><isbn>9781424483518</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFUFFLwzAYjIigzv0Bfckf6EzSJG0eZc45mPjgnh1fky810iWlDWL_vUMH3stxx3FwR8gtZwvOmbnfLN8eXxaCcb5QRhsmqzNyzaWQsi4Vl-f_QohLMh_HT3aE1kaZ-oq8r757HMIBYx5piBT6vptCbCm4L4gWHXWQgR5C_DWjO4YytgPkkCLNiX5MbkjFATOmIXWpDRY6OlqMMIQ03pALD92I8xPPyO5ptVs-F9vX9Wb5sC2CYblAUzEveaWtqFHXpnHgha28M0o55MAsSPCaVQqt96p2ZeNEo0vQaEyJdTkjd3-1ARH3_XEPDNP-dEf5A9_VVv0</recordid><startdate>201106</startdate><enddate>201106</enddate><creator>Hluchy, L.</creator><creator>Habala, O.</creator><creator>Krammer, P.</creator><creator>Seleng, M.</creator><creator>Tran, V.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201106</creationdate><title>Experiments in applying advanced data mining and integration to hydro-meteorological scenarios</title><author>Hluchy, L. ; Habala, O. ; Krammer, P. ; Seleng, M. ; Tran, V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-e970f4176c28e689bdaf2c7fd955de1a0ca4af6075ecff58d3bd2b63a6e993e83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Data mining</topic><topic>Data models</topic><topic>Predictive models</topic><topic>Radar imaging</topic><topic>Reservoirs</topic><topic>Temperature measurement</topic><toplevel>online_resources</toplevel><creatorcontrib>Hluchy, L.</creatorcontrib><creatorcontrib>Habala, O.</creatorcontrib><creatorcontrib>Krammer, P.</creatorcontrib><creatorcontrib>Seleng, M.</creatorcontrib><creatorcontrib>Tran, V.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hluchy, L.</au><au>Habala, O.</au><au>Krammer, P.</au><au>Seleng, M.</au><au>Tran, V.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Experiments in applying advanced data mining and integration to hydro-meteorological scenarios</atitle><btitle>Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services</btitle><stitle>ICSDM</stitle><date>2011-06</date><risdate>2011</risdate><spage>279</spage><epage>284</epage><pages>279-284</pages><isbn>1424483522</isbn><isbn>9781424483525</isbn><eisbn>1424483514</eisbn><eisbn>1424483506</eisbn><eisbn>9781424483501</eisbn><eisbn>9781424483518</eisbn><abstract>We present the results of applying advanced data integration and data mining (DMI) technology, developed in the FP7 project ADMIRE, to a set of hydro-meteorological pilot scenarios. The DMI technology includes a data processing architecture and its implementation by a set of tools, and a new DMI process definition language called DISPEL. It is based on the popular OGSA-DAI framework. The pilot scenarios were defined by hydrological and meteorological experts and their aim is to try predict hydro-meteorological processes in cases, where standard physical models for the chosen geographical domain are not present, or give unsatisfactory results. The obtained results show that the application of ADMIRE DMI technology is beneficient to the domain experts.</abstract><pub>IEEE</pub><doi>10.1109/ICSDM.2011.5969047</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 1424483522
ispartof Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, 2011, p.279-284
issn
language eng
recordid cdi_ieee_primary_5969047
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Data mining
Data models
Predictive models
Radar imaging
Reservoirs
Temperature measurement
title Experiments in applying advanced data mining and integration to hydro-meteorological scenarios
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T15%3A07%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Experiments%20in%20applying%20advanced%20data%20mining%20and%20integration%20to%20hydro-meteorological%20scenarios&rft.btitle=Proceedings%202011%20IEEE%20International%20Conference%20on%20Spatial%20Data%20Mining%20and%20Geographical%20Knowledge%20Services&rft.au=Hluchy,%20L.&rft.date=2011-06&rft.spage=279&rft.epage=284&rft.pages=279-284&rft.isbn=1424483522&rft.isbn_list=9781424483525&rft_id=info:doi/10.1109/ICSDM.2011.5969047&rft.eisbn=1424483514&rft.eisbn_list=1424483506&rft.eisbn_list=9781424483501&rft.eisbn_list=9781424483518&rft_dat=%3Cieee_6IE%3E5969047%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-e970f4176c28e689bdaf2c7fd955de1a0ca4af6075ecff58d3bd2b63a6e993e83%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5969047&rfr_iscdi=true