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dc.contributor.authorMöller, Knuden
dc.contributor.authorHausenblas, Michaelen
dc.contributor.authorCyganiak, Richarden
dc.contributor.authorHandschuh, Siegfrieden
dc.date.accessioned2010-05-20T14:22:58Zen
dc.date.available2010-05-20T14:22:58Zen
dc.date.issued2010en
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.identifier.urihttp://hdl.handle.net/10379/1110en
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.formatapplication/pdfen
dc.language.isoenen
dc.subjectUsage patternsen
dc.subjectAccessen
dc.subjectWeb of dataen
dc.subjectLinked dataen
dc.subjectDERIen
dc.titleLearning from Linked Open Data Usage: Patterns & Metricsen
dc.typeConference paperen
dc.description.peer-reviewedpeer-revieweden
dc.contributor.funderLíon 2en
nui.item.downloads1146


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