Semantic Annotation of Maps Through Knowledge Provenance
Identifieur interne : 000060 ( Istex/Corpus ); précédent : 000059; suivant : 000061Semantic Annotation of Maps Through Knowledge Provenance
Auteurs : Nicholas Del Rio ; Paulo Pinheiro Da Silva ; Q. Gates ; Leonardo SalayandiaSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: Maps are artifacts often derived from multiple sources of data, e.g., sensors, and processed by multiple methods, e.g., gridding and smoothing algorithms. As a result, complex metadata may be required to describe maps semantically. This paper presents an approach to describe maps by annotating associated provenance. Knowledge provenance can represent a semantic annotation mechanism that is more scalable than direct annotation of map. Semantic annotation of maps through knowledge provenance provides several benefits to end users. For example, a user study is presented showing that scientists with different levels of expertise and background are able to evaluate the quality of maps by analyzing their knowledge provenance information.
Url:
DOI: 10.1007/978-3-540-76876-0_2
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ISTEX:ADBFDF11C1F8870DE4B9BF7D61316DD43A1437DBLe document en format XML
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As a result, complex metadata may be required to describe maps semantically. This paper presents an approach to describe maps by annotating associated provenance. Knowledge provenance can represent a semantic annotation mechanism that is more scalable than direct annotation of map. Semantic annotation of maps through knowledge provenance provides several benefits to end users. For example, a user study is presented showing that scientists with different levels of expertise and background are able to evaluate the quality of maps by analyzing their knowledge provenance information.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Nicholas Del Rio</name><affiliations><json:string>The University of Texas at El Paso, Computer Science, 500 W. 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Robotics)</BookSubject><BookSubject Code="I18040" Priority="4" Type="Secondary">Information Systems Applications (incl.Internet)</BookSubject><BookSubject Code="W26007" Priority="5" Type="Secondary">Business Information Systems</BookSubject><BookSubject Code="G13007" Priority="6" Type="Secondary">Computer Applications in Geosciences</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup></BookInfo><BookHeader><EditorGroup><Editor><EditorName DisplayOrder="Western"><GivenName>Frederico</GivenName><FamilyName>Fonseca</FamilyName></EditorName><Contact><Email>fredfonseca@ist.psu.edu</Email></Contact></Editor><Editor><EditorName DisplayOrder="Western"><GivenName>M.</GivenName><GivenName>Andrea</GivenName><FamilyName>Rodríguez</FamilyName></EditorName><Contact><Email>andrea@udec.cl</Email></Contact></Editor><Editor><EditorName DisplayOrder="Western"><GivenName>Sergei</GivenName><FamilyName>Levashkin</FamilyName></EditorName><Contact><Email>sergei@cic.ipn.mx</Email></Contact></Editor></EditorGroup></BookHeader><Part ID="Part1"><PartInfo TocLevels="0"><PartID>1</PartID><PartSequenceNumber>1</PartSequenceNumber><PartTitle>Models and Languages for Geo-Ontologies</PartTitle><PartChapterCount>3</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>GeoSpatial Semantics</BookTitle></PartContext></PartInfo><Chapter ID="Chap2" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingStyle="Unnumbered" TocLevels="0"><ChapterID>2</ChapterID><ChapterDOI>10.1007/978-3-540-76876-0_2</ChapterDOI><ChapterSequenceNumber>2</ChapterSequenceNumber><ChapterTitle Language="En">Semantic Annotation of Maps Through Knowledge Provenance</ChapterTitle><ChapterFirstPage>20</ChapterFirstPage><ChapterLastPage>35</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2007</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>1</PartID><BookID>978-3-540-76876-0</BookID><BookTitle>GeoSpatial Semantics</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Nicholas</GivenName><Particle>Del</Particle><FamilyName>Rio</FamilyName></AuthorName><Contact><Email>ndel2@miners.utep.edu</Email></Contact></Author><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Paulo</GivenName><FamilyName>Pinheiro da Silva</FamilyName></AuthorName><Contact><Email>paulo@utep.edu</Email></Contact></Author><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Ann</GivenName><GivenName>Q.</GivenName><FamilyName>Gates</FamilyName></AuthorName><Contact><Email>agates@utep.edu</Email></Contact></Author><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Leonardo</GivenName><FamilyName>Salayandia</FamilyName></AuthorName><Contact><Email>leonardo@utep.edu</Email></Contact></Author><Affiliation ID="Aff1"><OrgName>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968</OrgName><OrgAddress><Country>USA</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Maps are artifacts often derived from multiple sources of data, e.g., sensors, and processed by multiple methods, e.g., gridding and smoothing algorithms. As a result, complex metadata may be required to describe maps semantically. This paper presents an approach to describe maps by annotating associated provenance. Knowledge provenance can represent a semantic annotation mechanism that is more scalable than direct annotation of map. Semantic annotation of maps through knowledge provenance provides several benefits to end users. For example, a user study is presented showing that scientists with different levels of expertise and background are able to evaluate the quality of maps by analyzing their knowledge provenance information.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Semantic Annotation of Maps Through Knowledge Provenance</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Semantic Annotation of Maps Through Knowledge Provenance</title></titleInfo><name type="personal"><namePart type="given">Nicholas</namePart><namePart type="family">Del Rio</namePart><affiliation>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968, USA</affiliation><affiliation>E-mail: ndel2@miners.utep.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Paulo</namePart><namePart type="family">Pinheiro da Silva</namePart><affiliation>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968, USA</affiliation><affiliation>E-mail: paulo@utep.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Ann</namePart><namePart type="given">Q.</namePart><namePart type="family">Gates</namePart><affiliation>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968, USA</affiliation><affiliation>E-mail: agates@utep.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Leonardo</namePart><namePart type="family">Salayandia</namePart><affiliation>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968, USA</affiliation><affiliation>E-mail: leonardo@utep.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2007</dateIssued><copyrightDate encoding="w3cdtf">2007</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 lang="en">Abstract: Maps are artifacts often derived from multiple sources of data, e.g., sensors, and processed by multiple methods, e.g., gridding and smoothing algorithms. As a result, complex metadata may be required to describe maps semantically. This paper presents an approach to describe maps by annotating associated provenance. Knowledge provenance can represent a semantic annotation mechanism that is more scalable than direct annotation of map. Semantic annotation of maps through knowledge provenance provides several benefits to end users. For example, a user study is presented showing that scientists with different levels of expertise and background are able to evaluate the quality of maps by analyzing their knowledge provenance information.</abstract><relatedItem type="host"><titleInfo><title>GeoSpatial Semantics</title><subTitle>Second International Conference, GeoS 2007, Mexico City, Mexico, November 29-30, 2007. Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Frederico</namePart><namePart type="family">Fonseca</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">M.</namePart><namePart type="given">Andrea</namePart><namePart type="family">Rodríguez</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Sergei</namePart><namePart type="family">Levashkin</namePart><role><roleTerm type="text">editor</roleTerm></role></name><genre type="book-series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2007</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book-Subject-Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book-Subject-Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I18024">Database Management</topic><topic authority="SpringerSubjectCodes" authorityURI="I18030">Data Mining and Knowledge Discovery</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. 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