An e‐Science data infrastructure for simulations within Grid computing environment: methods, approaches and practice
Identifieur interne : 000466 ( Istex/Corpus ); précédent : 000465; suivant : 000467An e‐Science data infrastructure for simulations within Grid computing environment: methods, approaches and practice
Auteurs : Xiaoyu Yang ; Martin T. Dove ; Richard P. Bruin ; Andrew Walkingshaw ; Richard Sinclair ; Dan J. Wilson ; Peter Murray-RustSource :
- Concurrency and Computation: Practice and Experience [ 1532-0626 ] ; 2013-03-10.
Abstract
Grid‐based simulation usually involves large quantities of data at each stage of the simulation process. These data include simulation input and output files, intermediate results files, log and error files, associated metadata, and information capturing the processes that generate the data. The question of how to effectively store and manage data files within a Grid computing environment is increasingly becoming an important issue. This paper illustrates how we built a lightweight e‐Science infrastructure for data management within a Grid computing environment, including the integration of data curation activities into the entire Grid‐based simulation process. Rather than focusing on specific implementation details, we aim to identify the key issues and research challenges, describing how various existing technologies and tools can be best integrated to address these requirements and challenges. Although the case of quantum mechanical simulation of materials properties is used in the paper, much of the discussion is as generic as possible so that approaches, methods and practice (e.g. integrated approach, workflow taxonomy and development approach, simple but useful semantic annotation approach) can be applied to wider domains and disciplines to facilitat the digital research. A comparison between our approach and Cloud computing, and lessons learned in data management within the Grid computing environment, are also presented. Copyright © 2012 John Wiley & Sons, Ltd.
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DOI: 10.1002/cpe.2849
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Bruin</name><affiliation><mods:affiliation>Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK</mods:affiliation></affiliation></author><author><name sortKey="Walkingshaw, Andrew" sort="Walkingshaw, Andrew" uniqKey="Walkingshaw A" first="Andrew" last="Walkingshaw">Andrew Walkingshaw</name><affiliation><mods:affiliation>Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK</mods:affiliation></affiliation></author><author><name sortKey="Sinclair, Richard" sort="Sinclair, Richard" uniqKey="Sinclair R" first="Richard" last="Sinclair">Richard Sinclair</name><affiliation><mods:affiliation>Daresbury Laboratory, Science and Technologies Facilities Council, UK</mods:affiliation></affiliation></author><author><name sortKey="Wilson, Dan J" sort="Wilson, Dan J" uniqKey="Wilson D" first="Dan J." last="Wilson">Dan J. Wilson</name><affiliation><mods:affiliation>J. W. Goethe University, Frankfurt, Germany</mods:affiliation></affiliation></author><author><name sortKey="Murray Ust, Peter" sort="Murray Ust, Peter" uniqKey="Murray Ust P" first="Peter" last="Murray-Rust">Peter Murray-Rust</name><affiliation><mods:affiliation>Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Concurrency and Computation: Practice and Experience</title><title level="j" type="abbrev">Concurrency Computat.: Pract. Exper.</title><idno type="ISSN">1532-0626</idno><idno type="eISSN">1532-0634</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><date type="published" when="2013-03-10">2013-03-10</date><biblScope unit="volume">25</biblScope><biblScope unit="issue">3</biblScope><biblScope unit="page" from="385">385</biblScope><biblScope unit="page" to="409">409</biblScope></imprint><idno type="ISSN">1532-0626</idno></series><idno type="istex">66D3FE122A3E7348EE0C5014A65BEFD271BC3ACA</idno><idno type="DOI">10.1002/cpe.2849</idno><idno type="ArticleID">CPE2849</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1532-0626</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">Grid‐based simulation usually involves large quantities of data at each stage of the simulation process. These data include simulation input and output files, intermediate results files, log and error files, associated metadata, and information capturing the processes that generate the data. The question of how to effectively store and manage data files within a Grid computing environment is increasingly becoming an important issue. This paper illustrates how we built a lightweight e‐Science infrastructure for data management within a Grid computing environment, including the integration of data curation activities into the entire Grid‐based simulation process. Rather than focusing on specific implementation details, we aim to identify the key issues and research challenges, describing how various existing technologies and tools can be best integrated to address these requirements and challenges. Although the case of quantum mechanical simulation of materials properties is used in the paper, much of the discussion is as generic as possible so that approaches, methods and practice (e.g. integrated approach, workflow taxonomy and development approach, simple but useful semantic annotation approach) can be applied to wider domains and disciplines to facilitat the digital research. A comparison between our approach and Cloud computing, and lessons learned in data management within the Grid computing environment, are also presented. Copyright © 2012 John Wiley & Sons, Ltd.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Xiaoyu Yang</name><affiliations><json:string>Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK</json:string><json:string>Correspondence to: Xiaoyu Yang, Senior Member, Wolfson College, University of Cambridge, Barton Road, Cambridge, CB3 9BB, UK.E‐mail:</json:string><json:string>E-mail: kevin.x.yang@wolfsonemail.com</json:string></affiliations></json:item><json:item><name>Martin T. Dove</name><affiliations><json:string>Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK</json:string></affiliations></json:item><json:item><name>Richard P. 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These data include simulation input and output files, intermediate results files, log and error files, associated metadata, and information capturing the processes that generate the data. The question of how to effectively store and manage data files within a Grid computing environment is increasingly becoming an important issue. This paper illustrates how we built a lightweight e‐Science infrastructure for data management within a Grid computing environment, including the integration of data curation activities into the entire Grid‐based simulation process. Rather than focusing on specific implementation details, we aim to identify the key issues and research challenges, describing how various existing technologies and tools can be best integrated to address these requirements and challenges. Although the case of quantum mechanical simulation of materials properties is used in the paper, much of the discussion is as generic as possible so that approaches, methods and practice (e.g. integrated approach, workflow taxonomy and development approach, simple but useful semantic annotation approach) can be applied to wider domains and disciplines to facilitat the digital research. A comparison between our approach and Cloud computing, and lessons learned in data management within the Grid computing environment, are also presented. 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These data include simulation input and output files, intermediate results files, log and error files, associated metadata, and information capturing the processes that generate the data. The question of how to effectively store and manage data files within a Grid computing environment is increasingly becoming an important issue. This paper illustrates how we built a lightweight e‐Science infrastructure for data management within a Grid computing environment, including the integration of data curation activities into the entire Grid‐based simulation process. Rather than focusing on specific implementation details, we aim to identify the key issues and research challenges, describing how various existing technologies and tools can be best integrated to address these requirements and challenges. Although the case of quantum mechanical simulation of materials properties is used in the paper, much of the discussion is as generic as possible so that approaches, methods and practice (e.g. integrated approach, workflow taxonomy and development approach, simple but useful semantic annotation approach) can be applied to wider domains and disciplines to facilitat the digital research. A comparison between our approach and Cloud computing, and lessons learned in data management within the Grid computing environment, are also presented. Copyright © 2012 John Wiley & Sons, Ltd.</p></abstract><textClass><keywords scheme="keyword"><list><head>keywords</head><item><term>data infrastructure</term></item><item><term>e‐infrastructure</term></item><item><term>cyberinfrastructure</term></item><item><term>e‐Science</term></item><item><term>data curation</term></item><item><term>ontology</term></item><item><term>workflow</term></item></list></keywords></textClass><textClass><keywords scheme="Journal Subject"><list><head>article-category</head><item><term>Research Article</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2011-10-31">Received</change><change when="2012-04-01">Registration</change><change when="2012-06-06">Created</change><change when="2013-03-10">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><original>false</original><mimetype>text/plain</mimetype><extension>txt</extension><uri>https://api.istex.fr/document/66D3FE122A3E7348EE0C5014A65BEFD271BC3ACA/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component type="serialArticle" version="2.0" xml:lang="en" xml:id="cpe2849"><header xml:id="cpe2849-hdr-0001"><publicationMeta level="product"><doi>10.1002/(ISSN)1532-0634</doi><issn type="print">1532-0626</issn><issn type="electronic">1532-0634</issn><idGroup><id type="product" value="CPE"></id></idGroup><titleGroup><title type="main" sort="CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCE">Concurrency and Computation: Practice and Experience</title><title type="short">Concurrency Computat.: Pract. 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YANG <i>ET AL.</i></title><title type="short">E‐SCIENCE DATA INFRASTRUCTURE</title></titleGroup><creators><creator xml:id="cpe2849-cr-0001" creatorRole="author" affiliationRef="#cpe2849-aff-0001" corresponding="yes"><personName><givenNames>Xiaoyu</givenNames><familyName>Yang</familyName></personName></creator><creator xml:id="cpe2849-cr-0002" creatorRole="author" affiliationRef="#cpe2849-aff-0001"><personName><givenNames>Martin T.</givenNames><familyName>Dove</familyName></personName></creator><creator xml:id="cpe2849-cr-0003" creatorRole="author" affiliationRef="#cpe2849-aff-0001"><personName><givenNames>Richard P.</givenNames><familyName>Bruin</familyName></personName></creator><creator xml:id="cpe2849-cr-0004" creatorRole="author" affiliationRef="#cpe2849-aff-0002"><personName><givenNames>Andrew</givenNames><familyName>Walkingshaw</familyName></personName></creator><creator xml:id="cpe2849-cr-0005" creatorRole="author" affiliationRef="#cpe2849-aff-0003"><personName><givenNames>Richard</givenNames><familyName>Sinclair</familyName></personName></creator><creator xml:id="cpe2849-cr-0006" creatorRole="author" affiliationRef="#cpe2849-aff-0004"><personName><givenNames>Dan J.</givenNames><familyName>Wilson</familyName></personName></creator><creator xml:id="cpe2849-cr-0007" creatorRole="author" affiliationRef="#cpe2849-aff-0002"><personName><givenNames>Peter</givenNames><familyName>Murray‐Rust</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="cpe2849-aff-0001" countryCode="GB" type="organization"><orgDiv>Department of Earth Sciences</orgDiv><orgName>University of Cambridge</orgName><address><street>Downing Street</street><city>Cambridge CB2 3EQ</city><country>UK</country></address></affiliation><affiliation xml:id="cpe2849-aff-0002" countryCode="GB" type="organization"><orgDiv>Department of Chemistry</orgDiv><orgName>University of Cambridge</orgName><address><street>Lensfield Road</street><city>Cambridge CB2 1EW</city><country>UK</country></address></affiliation><affiliation xml:id="cpe2849-aff-0003" countryCode="GB" type="organization"><orgDiv>Daresbury Laboratory</orgDiv><orgName>Science and Technologies Facilities Council</orgName><address><country>UK</country></address></affiliation><affiliation xml:id="cpe2849-aff-0004" countryCode="DE" type="organization"><orgName>J. W. Goethe University</orgName><address><city>Frankfurt</city><country>Germany</country></address></affiliation></affiliationGroup><keywordGroup type="author"><keyword xml:id="cpe2849-kwd-0001">data infrastructure</keyword><keyword xml:id="cpe2849-kwd-0002">e‐infrastructure</keyword><keyword xml:id="cpe2849-kwd-0003">cyberinfrastructure</keyword><keyword xml:id="cpe2849-kwd-0004">e‐Science</keyword><keyword xml:id="cpe2849-kwd-0005">data curation</keyword><keyword xml:id="cpe2849-kwd-0006">ontology</keyword><keyword xml:id="cpe2849-kwd-0007">workflow</keyword></keywordGroup><abstractGroup><abstract type="main" xml:id="cpe2849-abs-0001"><title type="main">SUMMARY</title><p xml:id="cpe2849-para-0001">Grid‐based simulation usually involves large quantities of data at each stage of the simulation process. These data include simulation input and output files, intermediate results files, log and error files, associated metadata, and information capturing the processes that generate the data. The question of how to effectively store and manage data files within a Grid computing environment is increasingly becoming an important issue. This paper illustrates how we built a lightweight e‐Science infrastructure for data management within a Grid computing environment, including the integration of data curation activities into the entire Grid‐based simulation process. Rather than focusing on specific implementation details, we aim to identify the key issues and research challenges, describing how various existing technologies and tools can be best integrated to address these requirements and challenges. Although the case of quantum mechanical simulation of materials properties is used in the paper, much of the discussion is as generic as possible so that approaches, methods and practice (e.g. integrated approach, workflow taxonomy and development approach, simple but useful semantic annotation approach) can be applied to wider domains and disciplines to facilitat the digital research. A comparison between our approach and Cloud computing, and lessons learned in data management within the Grid computing environment, are also presented. Copyright © 2012 John Wiley & Sons, Ltd.</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>An e‐Science data infrastructure for simulations within Grid computing environment: methods, approaches and practice</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>E‐SCIENCE DATA INFRASTRUCTURE</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>An e‐Science data infrastructure for simulations within Grid computing environment: methods, approaches and practice</title></titleInfo><name type="personal"><namePart type="given">Xiaoyu</namePart><namePart type="family">Yang</namePart><affiliation>Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK</affiliation><affiliation>Correspondence to: Xiaoyu Yang, Senior Member, Wolfson College, University of Cambridge, Barton Road, Cambridge, CB3 9BB, UK.E‐mail:</affiliation><affiliation>E-mail: kevin.x.yang@wolfsonemail.com</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Martin T.</namePart><namePart type="family">Dove</namePart><affiliation>Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Richard P.</namePart><namePart type="family">Bruin</namePart><affiliation>Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Andrew</namePart><namePart type="family">Walkingshaw</namePart><affiliation>Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Richard</namePart><namePart type="family">Sinclair</namePart><affiliation>Daresbury Laboratory, Science and Technologies Facilities Council, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Dan J.</namePart><namePart type="family">Wilson</namePart><affiliation>J. W. Goethe University, Frankfurt, Germany</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Peter</namePart><namePart type="family">Murray‐Rust</namePart><affiliation>Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><dateIssued encoding="w3cdtf">2013-03-10</dateIssued><dateCreated encoding="w3cdtf">2012-06-06</dateCreated><dateCaptured encoding="w3cdtf">2011-10-31</dateCaptured><dateValid encoding="w3cdtf">2012-04-01</dateValid><copyrightDate encoding="w3cdtf">2013</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract>Grid‐based simulation usually involves large quantities of data at each stage of the simulation process. These data include simulation input and output files, intermediate results files, log and error files, associated metadata, and information capturing the processes that generate the data. The question of how to effectively store and manage data files within a Grid computing environment is increasingly becoming an important issue. This paper illustrates how we built a lightweight e‐Science infrastructure for data management within a Grid computing environment, including the integration of data curation activities into the entire Grid‐based simulation process. Rather than focusing on specific implementation details, we aim to identify the key issues and research challenges, describing how various existing technologies and tools can be best integrated to address these requirements and challenges. Although the case of quantum mechanical simulation of materials properties is used in the paper, much of the discussion is as generic as possible so that approaches, methods and practice (e.g. integrated approach, workflow taxonomy and development approach, simple but useful semantic annotation approach) can be applied to wider domains and disciplines to facilitat the digital research. A comparison between our approach and Cloud computing, and lessons learned in data management within the Grid computing environment, are also presented. Copyright © 2012 John Wiley & Sons, Ltd.</abstract><subject><genre>keywords</genre><topic>data infrastructure</topic><topic>e‐infrastructure</topic><topic>cyberinfrastructure</topic><topic>e‐Science</topic><topic>data curation</topic><topic>ontology</topic><topic>workflow</topic></subject><relatedItem type="host"><titleInfo><title>Concurrency and Computation: Practice and Experience</title></titleInfo><titleInfo type="abbreviated"><title>Concurrency Computat.: Pract. Exper.</title></titleInfo><genre type="journal">journal</genre><subject><genre>article-category</genre><topic>Research Article</topic></subject><identifier type="ISSN">1532-0626</identifier><identifier type="eISSN">1532-0634</identifier><identifier type="DOI">10.1002/(ISSN)1532-0634</identifier><identifier type="PublisherID">CPE</identifier><part><date>2013</date><detail type="volume"><caption>vol.</caption><number>25</number></detail><detail type="issue"><caption>no.</caption><number>3</number></detail><extent unit="pages"><start>385</start><end>409</end><total>25</total></extent></part></relatedItem><identifier type="istex">66D3FE122A3E7348EE0C5014A65BEFD271BC3ACA</identifier><identifier type="DOI">10.1002/cpe.2849</identifier><identifier type="ArticleID">CPE2849</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright © 2013 John Wiley & Sons, Ltd.Copyright © 2012 John Wiley & Sons, Ltd.</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource></recordInfo></mods></metadata><enrichments><json:item><type>multicat</type><uri>https://api.istex.fr/document/66D3FE122A3E7348EE0C5014A65BEFD271BC3ACA/enrichments/multicat</uri></json:item></enrichments><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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