Semantic Annotation of Maps Through Knowledge Provenance
Identifieur interne : 000F35 ( Main/Curation ); précédent : 000F34; suivant : 000F36Semantic Annotation of Maps Through Knowledge Provenance
Auteurs : Nicholas Del Rio [États-Unis] ; Paulo Pinheiro Da Silva [États-Unis] ; Q. Gates [États-Unis] ; Leonardo Salayandia [États-Unis]Source :
- 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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Gates</name><affiliation wicri:level="1"><country xml:lang="fr">États-Unis</country><wicri:regionArea>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968</wicri:regionArea><wicri:noRegion>500 W. University Ave. El Paso TX 79968</wicri:noRegion></affiliation><affiliation wicri:level="1"><country wicri:rule="url">États-Unis</country></affiliation></author><author><name sortKey="Salayandia, Leonardo" sort="Salayandia, Leonardo" uniqKey="Salayandia L" first="Leonardo" last="Salayandia">Leonardo Salayandia</name><affiliation wicri:level="1"><country xml:lang="fr">États-Unis</country><wicri:regionArea>The University of Texas at El Paso, Computer Science, 500 W. University Ave. El Paso TX 79968</wicri:regionArea><wicri:noRegion>500 W. University Ave. El Paso TX 79968</wicri:noRegion></affiliation><affiliation wicri:level="1"><country wicri:rule="url">États-Unis</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2007</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">ADBFDF11C1F8870DE4B9BF7D61316DD43A1437DB</idno><idno type="DOI">10.1007/978-3-540-76876-0_2</idno><idno type="ChapterID">2</idno><idno type="ChapterID">Chap2</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml: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.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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