Analysis and synthesis of metadata goals for scientific data
Identifieur interne : 000647 ( Istex/Corpus ); précédent : 000646; suivant : 000648Analysis and synthesis of metadata goals for scientific data
Auteurs : Craig Willis ; Jane Greenberg ; Hollie WhiteSource :
- Journal of the American Society for Information Science and Technology [ 1532-2882 ] ; 2012-08.
Abstract
The proliferation of discipline‐specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed‐methods content analysis and Greenberg's () metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata‐related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (p < .05). Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have “scheme harmonization” (compatibility and interoperability with related schemes) as an objective; schemes with the objective “abstraction” (a conceptual model exists separate from the technical implementation) also have the objective “sufficiency” (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective “data publication” do not have the objective “element refinement.” The analysis indicates that many metadata‐driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata‐related research, particularly in the context of recent funding agency policy changes.
Url:
DOI: 10.1002/asi.22683
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ISTEX:0D0A3C653502795376BC2DFD1E30E2B474C171E7Le document en format XML
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The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed‐methods content analysis and Greenberg's () metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata‐related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (p < .05). Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have “scheme harmonization” (compatibility and interoperability with related schemes) as an objective; schemes with the objective “abstraction” (a conceptual model exists separate from the technical implementation) also have the objective “sufficiency” (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective “data publication” do not have the objective “element refinement.” The analysis indicates that many metadata‐driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata‐related research, particularly in the context of recent funding agency policy changes.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Craig Willis</name><affiliations><json:string>Metadata Research Center, School of Library and Information Science, University of North Carolina, Chapel Hill, NC, Chapel Hill</json:string><json:string>E-mail: craig.willis@unc.edu</json:string></affiliations></json:item><json:item><name>Jane Greenberg</name><affiliations><json:string>Metadata Research Center, School of Library and Information Science, University of North Carolina, Chapel Hill, NC, Chapel Hill</json:string><json:string>E-mail: janeg@email.unc.edu</json:string></affiliations></json:item><json:item><name>Hollie White</name><affiliations><json:string>J. 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Schemes describing observational data are more likely to have “scheme harmonization” (compatibility and interoperability with related schemes) as an objective; schemes with the objective “abstraction” (a conceptual model exists separate from the technical implementation) also have the objective “sufficiency” (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective “data publication” do not have the objective “element refinement.” The analysis indicates that many metadata‐driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. 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href="http://psi.asis.org/digital/interdisciplinarity">interdisciplinarity</subject><subject href="http://psi.asis.org/digital/interoperability">interoperability</subject></subjectInfo><objectNameGroup><objectName elementName="appendix" displayTitle="no">Appendix</objectName></objectNameGroup><linkGroup><link type="toTypesetVersion" href="file:ASI.ASI22683.pdf"></link></linkGroup></publicationMeta><contentMeta><titleGroup><title type="main">Analysis and synthesis of metadata goals for scientific data</title></titleGroup><creators><creator affiliationRef="#asi22683-aff-0001" creatorRole="author" xml:id="asi22683-cr-0001"><personName><givenNames>Craig</givenNames><familyName>Willis</familyName></personName><contactDetails><email>craig.willis@unc.edu</email></contactDetails></creator><creator affiliationRef="#asi22683-aff-0001" creatorRole="author" xml:id="asi22683-cr-0002"><personName><givenNames>Jane</givenNames><familyName>Greenberg</familyName></personName><contactDetails><email>janeg@email.unc.edu</email></contactDetails></creator><creator affiliationRef="#asi22683-aff-0002" creatorRole="author" xml:id="asi22683-cr-0003"><personName><givenNames>Hollie</givenNames><familyName>White</familyName></personName><contactDetails><email>hollie.white@law.duke.edu</email></contactDetails></creator></creators><affiliationGroup><affiliation countryCode="US" xml:id="asi22683-aff-0001"><orgDiv>Metadata Research Center</orgDiv><orgDiv>School of Library and Information Science</orgDiv><orgName>University of North Carolina, Chapel Hill</orgName><address><city>Chapel Hill</city><countryPart>NC</countryPart></address></affiliation><affiliation countryCode="US" xml:id="asi22683-aff-0002"><orgDiv>J. Michael Goodson Law Library</orgDiv><orgName>Duke University</orgName><address><city>Durham</city><countryPart>NC</countryPart></address></affiliation></affiliationGroup><keywordGroup type="author"><keyword xml:id="asi22683-kwd-0001">metadata</keyword><keyword xml:id="asi22683-kwd-0002">data</keyword></keywordGroup><abstractGroup> <abstract type="main"><p>The proliferation of discipline‐specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the <i>domains</i>, <i>objectives</i>, and <i>architectures</i> of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed‐methods content analysis and <fc>G</fc>reenberg's (<link href="#asi22683-bib-0020"></link>) metadata objectives, principles, domains, and architectural layout (<fc>MODAL</fc>) framework, and derived 22 metadata‐related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (<i><fc>p</fc></i> < .05).</p><p>Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have “scheme harmonization” (compatibility and interoperability with related schemes) as an objective; schemes with the objective “abstraction” (a conceptual model exists separate from the technical implementation) also have the objective “sufficiency” (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective “data publication” do not have the objective “element refinement.” The analysis indicates that many metadata‐driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata‐related research, particularly in the context of recent funding agency policy changes.</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Analysis and synthesis of metadata goals for scientific data</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Analysis and synthesis of metadata goals for scientific data</title></titleInfo><name type="personal"><namePart type="given">Craig</namePart><namePart type="family">Willis</namePart><affiliation>Metadata Research Center, School of Library and Information Science, University of North Carolina, Chapel Hill, NC, Chapel Hill</affiliation><affiliation>E-mail: craig.willis@unc.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jane</namePart><namePart type="family">Greenberg</namePart><affiliation>Metadata Research Center, School of Library and Information Science, University of North Carolina, Chapel Hill, NC, Chapel Hill</affiliation><affiliation>E-mail: janeg@email.unc.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Hollie</namePart><namePart type="family">White</namePart><affiliation>J. Michael Goodson Law Library, Duke University, NC, Durham</affiliation><affiliation>E-mail: hollie.white@law.duke.edu</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">2012-08</dateIssued><dateCreated encoding="w3cdtf">2012-04-03</dateCreated><dateCaptured encoding="w3cdtf">2011-11-30</dateCaptured><dateValid encoding="w3cdtf">2012-02-19</dateValid><copyrightDate encoding="w3cdtf">2012</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>The proliferation of discipline‐specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed‐methods content analysis and Greenberg's () metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata‐related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (p < .05). Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have “scheme harmonization” (compatibility and interoperability with related schemes) as an objective; schemes with the objective “abstraction” (a conceptual model exists separate from the technical implementation) also have the objective “sufficiency” (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective “data publication” do not have the objective “element refinement.” The analysis indicates that many metadata‐driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata‐related research, particularly in the context of recent funding agency policy changes.</abstract><subject><genre>keywords</genre><topic>metadata</topic><topic>data</topic></subject><relatedItem type="host"><titleInfo><title>Journal of the American Society for Information Science and Technology</title></titleInfo><titleInfo type="abbreviated"><title>J Am Soc Inf Sci Tec</title></titleInfo><genre type="journal">journal</genre><subject><genre>index-terms</genre><topic authorityURI="http://psi.asis.org/digital/metadata">metadata</topic><topic authorityURI="http://psi.asis.org/digital/scientific+and+technical+information">scientific and technical information</topic><topic authorityURI="http://psi.asis.org/digital/data+models">data models</topic><topic authorityURI="http://psi.asis.org/digital/interdisciplinarity">interdisciplinarity</topic><topic authorityURI="http://psi.asis.org/digital/interoperability">interoperability</topic></subject><subject><genre>article-category</genre><topic>RESEARCH ARTICLE</topic></subject><identifier type="ISSN">1532-2882</identifier><identifier type="eISSN">1532-2890</identifier><identifier type="DOI">10.1002/(ISSN)1532-2890</identifier><identifier type="PublisherID">ASI</identifier><part><date>2012</date><detail type="volume"><caption>vol.</caption><number>63</number></detail><detail type="issue"><caption>no.</caption><number>8</number></detail><extent unit="pages"><start>1505</start><end>1520</end><total>16</total></extent></part></relatedItem><identifier type="istex">0D0A3C653502795376BC2DFD1E30E2B474C171E7</identifier><identifier type="DOI">10.1002/asi.22683</identifier><identifier type="ArticleID">ASI22683</identifier><accessCondition type="use and reproduction" contentType="copyright">© 2012 ASIS&T© 2012 ASIS&T</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource></recordInfo></mods></metadata><enrichments><json:item><type>multicat</type><uri>https://api.istex.fr/document/0D0A3C653502795376BC2DFD1E30E2B474C171E7/enrichments/multicat</uri></json:item></enrichments><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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