LinkedDataLens: linked data as a network of networks

Authors:
Yolanda Gil;Paul Groth
Affiliations:
University of Southern California, Marina del Rey, USA;VU University Amsterdam, Amsterdam, Netherlands
Venue:
Proceedings of the sixth international conference on Knowledge capture
Year:
2011

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Abstract

With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for analyzing and using the Web of Data based on extracting and analyzing thematic subsets of it. We view the Web of Data as a "network of networks" from which to extract meaningful subsets that can be converted them into self-contained networks to be further analyzed and reused. These extracted networks can then be analyzed through network analysis and discovery algorithms, and the results of these analyses can be published back on the Web of Data. We describe LinkedDataLens, an implementation of this framework that uses the Wings workflow system to represent multi-step network extraction and analysis processes.