Abstract
Little is known about the dynamics of Linked Data, primarily because there have been few, if any, suitable collections of data made available for analysis of how Linked Data documents evolve over time. We aim to address this issue. We propose the Dynamic Linked Data Observatory, which provides the community with such a collection, monitoring a fixed set of Linked Data documents at weekly intervals. We have now collected eight months of raw data comprising weekly snapshots of eighty thousand Linked Data documents. Having published results characterising the high-level dynamics of Linked Data, we now wish to disseminate results: we wish to investigate how results from our experiment might benefit the community and what online services and statistics (relating to Linked Data dynamics) would be most useful for us to provide.
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Käfer, T., Abdelrahman, A., Umbrich, J., O’Byrne, P., Hogan, A.: Observing Linked Data Dynamics. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 213–227. Springer, Heidelberg (2013)
Käfer, T., Umbrich, J., Hogan, A., Polleres, A.: DyLDO: Towards a Dynamic Linked Data Observatory. In: LDOW at WWW. CEUR-WS, vol. 937 (2012)
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Käfer, T., Abdelrahman, A., Umbrich, J., O’Byrne, P., Hogan, A. (2013). Exploring the Dynamics of Linked Data. In: Cimiano, P., Fernández, M., Lopez, V., Schlobach, S., Völker, J. (eds) The Semantic Web: ESWC 2013 Satellite Events. ESWC 2013. Lecture Notes in Computer Science, vol 7955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41242-4_52
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DOI: https://doi.org/10.1007/978-3-642-41242-4_52
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