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Section: New Results

Multi-Criteria Experimental Classification of Distributed SPARQL Evaluators

In this work [13], we provide a new perspective on distributed sparql evaluators, based on a multi-criteria ranking obtained through extensive experiments. Specifically, we propose a set of five principal features which we use to rank evaluators. Each system exhibits a particular combination of these features. Similarly, the various requirements of practical use cases can also be decomposed in terms of these features. Our suggested set of features provides a more comprehensive description of the behavior of a distributed evaluator when compared to traditional performance metrics. We show how it helps in more accurately evaluating to which extent a given system is appropriate for a given use case. For this purpose, we systematically benchmarked a panel of 10 state-of-the-art implementations. We ranked them using this reading grid to pinpoint the advantages and limitations of current sparql evaluation systems.