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dc.contributor.authorMöller, Knuden
dc.contributor.authorHausenblas, Michaelen
dc.contributor.authorCyganiak, Richarden
dc.contributor.authorHandschuh, Siegfrieden
dc.identifier.citationKnud Möller, Michael Hausenblas, Richard Cyganiak, Siegfried Handschuh, Gunnar Grimnes "Learning from Linked Open Data Usage: Patterns & Metrics", Web Science Conference 2010, 2010.en
dc.description.abstractAlthough the cloud of Linked Open Data has been growing continuously for several years, little is known about the particular features of linked data usage. Motivating why it is important to understand the usage of Linked Data, we describe typical linked data usage scenarios and contrast the so derived requirement with conventional server access analysis. Then, we report on usage patterns found through an in-depth analysis of access logs of four popular LOD datasets. Eventually, based on the usage patterns we found in the analysis, we propose metrics for assessing Linked Data usage from the human and the machine perspective, taking into account different agent types and resource representations.en
dc.subjectUsage patternsen
dc.subjectWeb of dataen
dc.subjectLinked dataen
dc.titleLearning from Linked Open Data Usage: Patterns & Metricsen
dc.typeConference Paperen
dc.contributor.funderLíon 2en

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