19 research outputs found

    A schema-based P2P network to enable publish-subscribe for multimedia content in open hypermedia systems

    No full text
    Open Hypermedia Systems (OHS) aim to provide efficient dissemination, adaptation and integration of hyperlinked multimedia resources. Content available in Peer-to-Peer (P2P) networks could add significant value to OHS provided that challenges for efficient discovery and prompt delivery of rich and up-to-date content are successfully addressed. This paper proposes an architecture that enables the operation of OHS over a P2P overlay network of OHS servers based on semantic annotation of (a) peer OHS servers and of (b) multimedia resources that can be obtained through the link services of the OHS. The architecture provides efficient resource discovery. Semantic query-based subscriptions over this P2P network can enable access to up-to-date content, while caching at certain peers enables prompt delivery of multimedia content. Advanced query resolution techniques are employed to match different parts of subscription queries (subqueries). These subscriptions can be shared among different interested peers, thus increasing the efficiency of multimedia content dissemination

    Peer-based query rewriting in SPARQL for semantic integration of linked data

    Get PDF
    In this proposal we address the problem of ontology-based SPARQL query answering over distributed Linked Data sources, where the ontology is given by conjunctive mappings between the source schemas in a peer-to-peer fashion and by equality constraints between constants. In our setting, the data is not materialised in a single datastore: it is accessed in a distributed environment through SPARQL endpoints. We aim to achieve query answering by generating the perfect rewriting of the original query and then processing the rewritten query over distributed SPARQL endpoints. We identify a subset of ontology constraints that enjoy the first-order rewritability property and we perform preliminary empirical evaluation taking into account such restricted constraints only. For future work, we aim to tackle the query answering problem in the general case

    Evaluating Conjunctive Triple Pattern Queries over Large Structured Overlay Networks

    Get PDF
    We study the problem of evaluating conjunctive queries com- posed of triple patterns over RDF data stored in distributed hash tables. Our goal is to develop algorithms that scale to large amounts of RDF data, distribute the query processing load evenly and incur little network traffic. We present and evaluate two novel query processing algorithms with these possibly conflicting goals in mind. We discuss the various tradeoffs that occur in our setting through a detailed experimental eval- uation of the proposed algorithms

    Peer-to-peer semantic integration of linked data

    Get PDF
    We propose a framework for peer-based integration of linked data sets, where the semantic relationships between data at different peers are expressed through mappings. We provide the theoretical foundations for such a setting and we devise an algorithm for processing graph pattern queries, discussing its complexity and scalability

    Distributed Semantic Web Data Management in HBase and MySQL Cluster

    Full text link
    Various computing and data resources on the Web are being enhanced with machine-interpretable semantic descriptions to facilitate better search, discovery and integration. This interconnected metadata constitutes the Semantic Web, whose volume can potentially grow the scale of the Web. Efficient management of Semantic Web data, expressed using the W3C's Resource Description Framework (RDF), is crucial for supporting new data-intensive, semantics-enabled applications. In this work, we study and compare two approaches to distributed RDF data management based on emerging cloud computing technologies and traditional relational database clustering technologies. In particular, we design distributed RDF data storage and querying schemes for HBase and MySQL Cluster and conduct an empirical comparison of these approaches on a cluster of commodity machines using datasets and queries from the Third Provenance Challenge and Lehigh University Benchmark. Our study reveals interesting patterns in query evaluation, shows that our algorithms are promising, and suggests that cloud computing has a great potential for scalable Semantic Web data management.Comment: In Proc. of the 4th IEEE International Conference on Cloud Computing (CLOUD'11

    Publish and subscribe for RDF in enterprise value networks

    Get PDF
    Sharing information securely between business partners and managing large supply chains effciently will be a crucial competitive advantage for enterprises in the near future. In this paper, we present a concept that allows for building value networks between business partners in a distributed manner. Companies are able to publish Linked Data which participants of the network can clone and subscribe to. Subscribers get noticed as soon as new information becomes available. This provides a technical infrastructure for business communication acts such as supply chain communication or master data management. In addition to the conceptual analysis, we provide an implementation enabling companies to create such dynamic semantic value networks

    Distributed storage and queryng techniques for a semantic web of scientific workflow provenance

    Get PDF
    In scientific workflow environments, scientists depend on provenance, which records the history of an experiment. Resource Description Framework is frequently used to represent provenance based on vocabularies such as the Open Provenance Model. For complex scientific workflows that generate large amounts of RDF triples, single-machine provenance management becomes inadequate over time. In this thesis, we research how HBase capabilities can be leveraged for distributed storage and querying of provenance data represented in RDF. We architect the ProvBase system that incorporates an HBase/Hadoop backend, propose a storage schema to hold provenance triples, and design querying algorithms to evaluate SPARQL queries in the system. We conduct an experimental study to show the feasibility of our approach

    Distributed Semantic Web data management in HBase and MySQL cluster

    Get PDF
    Various computing and data resources on the Web are being enhanced with machine-interpretable semantic descriptions to facilitate better search, discovery and integration. This interconnected metadata constitutes the Semantic Web, whose volume can potentially grow the scale of the Web. Efficient management of Semantic Web data, expressed using the W3C\u27s Resource Description Framework (RDF), is crucial for supporting new data-intensive, semantics-enabled applications. In this work, we study and compare two approaches to distributed RDF data management based on emerging cloud computing technologies and traditional relational database clustering technologies. In particular, we design distributed RDF data storage and querying schemes for HBase and MySQL Cluster and conduct an empirical comparison of these approaches on a cluster of commodity machines using datasets and queries from the Third Provenance Challenge and Lehigh University Benchmark. Our study reveals interesting patterns in query evaluation, shows that our algorithms are promising, and suggests that cloud computing has a great potential for scalable Semantic Web data management

    RDF Data Indexing and Retrieval: A survey of Peer-to-Peer based solutions

    Get PDF
    The Semantic Web enables the possibility to model, create and query resources found on the Web. Enabling the full potential of its technologies at the Internet level requires infrastructures that can cope with scalability challenges and support various types of queries. The attractive features of the Peer-to-Peer (P2P) communication model such as decentralization, scalability, fault-tolerance seems to be a natural solution to deal with these challenges. Consequently, the combination of the Semantic Web and the P2P model can be a highly innovative attempt to harness the strengths of both technologies and come up with a scalable infrastructure for RDF data storage and retrieval. In this respect, this survey details the research works that adopt this combination and gives an insight on how to deal with the RDF data at the indexing and querying levels.Le Web Sémantique permet de modéliser, créer et faire des requêtes sur les ressources disponibles sur le Web. Afin de permettre à ses technologies d'exploiter leurs potentiels à l'échelle de l'Internet, il est nécessaire qu'elles reposent sur des infrastructures qui puissent passer à l'échelle ainsi que de répondre aux exigences d'expressivité des types de requêtes qu'elles offrent. Les bonnes propriétés qu'offrent les dernières générations de systèmes pair-à- pair en termes de décentralisation, de tolérance aux pannes ainsi que de passage à l'échelle en font d'eux des candidats prometteurs. La combinaison du modèle pair-à-pair et des technologies du Web Sémantique est une tentative innovante ayant pour but de fournir une infrastructure capable de passer à l'échelle et pouvant stocker et rechercher des données de type RDF. Dans ce contexte, ce rapport présente un état de l'art et discute en détail des travaux autour de systèmes pair-à-pair qui traitent des données de type RDF à large échelle. Nous détaillons leurs mécanismes d'indexation de données ainsi que le traitement des divers types de requêtes offerts

    SPARQL Query Optimization on Top of DHTs

    Full text link
    corecore