Evaluating Systems and Benchmarks for Archiving Evolving Linked Datasets

Tracking #: 1605-2817

This paper is currently under review
Irini Fundulaki
Vassilis Papakonstantinou
Yannis Roussakis
Giorgos Flouris
Kostas Stefanidis1

Responsible editor: 
Ruben Verborgh

Submission type: 
Full Paper
As dynamicity is an indispensable part of Linked Data, which are constantly evolving at both schema and instance level, there is a clear need for archiving systems that are able to support the efficient storage and querying of such data. The purpose of this paper is to provide a framework for systematically studying the state-of-art RDF archiving systems and the different types of queries that such systems should support. Specifically, we describe the strategies that archiving systems follow for storing multiple versions of a dataset, and detail the characteristics of the archiving benchmarks. Moreover, we evaluate the archiving systems, and present results regarding their performance. Finally, we highlight difficulties and open issues arisen during experimentation in order to serve as a springboard for researchers in the Linked Data community.
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