Observing linked data dynamics

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Abstract

In this paper, we present the design and first results of the Dynamic Linked Data Observatory: a long-term experiment to monitor the two-hop neighbourhood of a core set of eighty thousand diverse Linked Data documents on a weekly basis. We present the methodology used for sampling the URIs to monitor, retrieving the documents, and further crawling part of the two-hop neighbourhood. Having now run this experiment for six months, we analyse the dynamics of the monitored documents over the data collected thus far. We look at the estimated lifespan of the core documents, how often they go on-line or off-line, how often they change; we further investigate domain-level trends. Next we look at changes within the RDF content of the core documents across the weekly snapshots, examining the elements (i.e., triples, subjects, predicates, objects, classes) that are most frequently added or removed. Thereafter, we look at how the links between dereferenceable documents evolves over time in the two-hop neighbourhood. © 2013 Springer-Verlag Berlin Heidelberg.

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APA

Käfer, T., Abdelrahman, A., Umbrich, J., O’Byrne, P., & Hogan, A. (2013). Observing linked data dynamics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7882 LNCS, pp. 213–227). Springer Verlag. https://doi.org/10.1007/978-3-642-38288-8_15

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