ARAN - Access to Research at NUI Galway

Learning from Linked Open Data Usage: Patterns & Metrics

ARAN - Access to Research at NUI Galway

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dc.contributor.author Möller, Knud en
dc.contributor.author Hausenblas, Michael en
dc.contributor.author Cyganiak, Richard en
dc.contributor.author Handschuh, Siegfried en
dc.date.accessioned 2010-05-20T14:22:58Z en
dc.date.available 2010-05-20T14:22:58Z en
dc.date.issued 2010 en
dc.identifier.citation Knud 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.uri http://hdl.handle.net/10379/1110 en
dc.description.abstract Although 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.format application/pdf en
dc.language.iso en en
dc.subject Usage patterns en
dc.subject Access en
dc.subject Web of data en
dc.subject Linked data en
dc.subject DERI en
dc.title Learning from Linked Open Data Usage: Patterns & Metrics en
dc.type Conference paper en
dc.description.peer-reviewed peer-reviewed en
dc.contributor.funder Líon 2 en

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