Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely-coupled peers. We present our divide-conquer-swap strategy and show that this model converges towards completeness.Within this strategy, we address the problem of making distributed reasoning scalable and load-balanced. We present SpeedDate, a routing strategy that combines data clustering with random exchanges. The random exchanges ensure load balancing, while the data clustering attempts to maximise efficiency. SpeedDate is compared against random and deterministic (DHT-like) approaches, on performance and load-balancing. We simulate parameters such as system size, data distribution, churn rate, and network topology. The results indicate that SpeedDate is near-optimally balanced, performs in the same order of magnitude as a DHT-like approach, and has an average throughput per node that scales with √ i for i items in the system. We evaluate our overall Marvin system for performance, scalability, load balancing and efficiency.
Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely-coupled peers. We present our divide-conquer-swap strategy and show that this model converges towards completeness.Within this strategy, we address the problem of making distributed reasoning scalable and load-balanced. We present SpeedDate, a routing strategy that combines data clustering with random exchanges. The random exchanges ensure load balancing, while the data clustering attempts to maximise efficiency. SpeedDate is compared against random and deterministic (DHT-like) approaches, on performance and load-balancing. We simulate parameters such as system size, data distribution, churn rate, and network topology. The results indicate that SpeedDate is near-optimally balanced, performs in the same order of magnitude as a DHT-like approach, and has an average throughput per node that scales with √ i for i items in the system. We evaluate our overall Marvin system for performance, scalability, load balancing and efficiency.
In this paper we outline the design and implementation of the eDialogos Consensus process and platform to support wide-scale collaborative decision making. We present the design space and choices made and perform a conceptual alignement of the domains this space entails, based on the use of the eDialogos Consensus ontology as a crystallization point for platform design and implementation as well as interoperability with existing solutions. We also present a metric for calculating agreement on the issues under debate in the platform, incorporating argumentation structure and user feedback.
In this paper we describe the application of various Semantic Web technologies and their combination with emerging Web 2.0 use patterns in the eParticipation domain and show how they are used in an operational system for the Regional Government of the Prefecture of Samos, Greece. We present parts of the system that are based on Semantic Web technology and how they are merged with a Web 2.0 philosophy and explain the benefits of this approach, as showcased by applications for annotating, searching, browsing and cross-referencing content in eParticipation communities.
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