904 research outputs found

    Implementing Database Coordination in P2P Networks

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    We are interested in the interaction of databases in Peer-to-Peer (P2P) networks. In this paper we propose a new solution for P2P databases, that we call database coordination. We see coordination as managing semantic interdependencies among databases at runtime. We propose a data coordination model where the notions of Interest Groups and Acquaintances play the most crucial role. Interest groups support the formation of peers according to data models they have in common; and acquaintances allow for peers inter-operation. Finally, we present an architecture supporting database coordination and show how it is implemented on top of JXTA

    Linked education: interlinking educational resources and the web of data

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    Research on interoperability of technology-enhanced learning (TEL) repositories throughout the last decade has led to a fragmented landscape of competing approaches, such as metadata schemas and interface mechanisms. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de-facto standard for sharing data on the Web and offers a large potential to solve interoperability issues in the field of TEL. In this paper, we describe a general approach to exploit the wealth of already existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain. This approach has been implemented in the context of the mEducator project where data from a number of open TEL data repositories has been integrated, exposed and enriched by following Linked Data principles

    Peer - Mediated Distributed Knowledge Management

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    Distributed Knowledge Management is an approach to knowledge management based on the principle that the multiplicity (and heterogeneity) of perspectives within complex organizations is not be viewed as an obstacle to knowledge exploitation, but rather as an opportunity that can foster innovation and creativity. Despite a wide agreement on this principle, most current KM systems are based on the idea that all perspectival aspects of knowledge should be eliminated in favor of an objective and general representation of knowledge. In this paper we propose a peer-to-peer architecture (called KEx), which embodies the principle above in a quite straightforward way: (i) each peer (called a K-peer) provides all the services needed to create and organize "local" knowledge from an individual's or a group's perspective, and (ii) social structures and protocols of meaning negotiation are introduced to achieve semantic coordination among autonomous peers (e.g., when searching documents from other K-peers). A first version of the system, called KEx, is imple-mented as a knowledge exchange level on top of JXTA

    Schema matching in a peer-to-peer database system

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    Includes bibliographical references (p. 112-118).Peer-to-peer or P2P systems are applications that allow a network of peers to share resources in a scalable and efficient manner. My research is concerned with the use of P2P systems for sharing databases. To allow data mediation between peers' databases, schema mappings need to exist, which are mappings between semantically equivalent attributes in different peers' schemas. Mappings can either be defined manually or found semi-automatically using a technique called schema matching. However, schema matching has not been used much in dynamic environments, such as P2P networks. Therefore, this thesis investigates how to enable effective semi-automated schema matching within a P2P network

    A P2P Integration Architecture for Protein Resources

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    The availability of a direct pathway from a primary sequence (denovo or DNA derived) to macromolecular structure to biological function using computer-based tools is the ultimate goal for a protein scientist. Today\u27s state of the art protein resources and on-going research and experiments provide the raw data that can enable protein scientists to achieve at least some steps of this goal. Thus, protein scientists are looking towards taking their benchtop research from the specific to a much broader base of using the large resources of available electronic information. However, currently the burden falls on the scientist to manually interface with each data resource, integrate the required information, and then finally interpret the results. Their discoveries are impeded by the lack of tools that can not only bring integrated information from several known data resources, but also weave in information as it is discovered and brought online by other research groups. We propose a novel peer-to-peer based architecture that allows protein scientists to share resources in the form of data and tools within their community, facilitating ad hoc, decentralized sharing of data. In this paper, we present an overview of this integration architecture and briefly describe the tools that are essential to this framework
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