Abstract. DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human-and machine-consumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

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As the Web of Data is growing at an ever increasing speed, the lack of reliable query solutions for live public data becomes apparent. sparql implementations have matured and deliver impressive performance for public sparql endpoints, yet poor availability-especially under high loads-prevents their use in real-world applications. We propose to tackle this availability problem by defining triple pattern fragments, a specific kind of Linked Data Fragments that enable low-cost publication of queryable data by moving intelligence from the server to the client. This paper formalizes the Linked Data Fragments concept, introduces a client-side sparql query processing algorithm that uses a dynamic iterator pipeline, and verifies servers' availability under load. The results indicate that, at the cost of lower performance, query techniques with triple pattern fragments lead to high availability, thereby allowing for reliable applications on top of public, queryable Linked Data.

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