41,679 research outputs found

    Protocols for Integrity Constraint Checking in Federated Databases

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    A federated database is comprised of multiple interconnected database systems that primarily operate independently but cooperate to a certain extent. Global integrity constraints can be very useful in federated databases, but the lack of global queries, global transaction mechanisms, and global concurrency control renders traditional constraint management techniques inapplicable. This paper presents a threefold contribution to integrity constraint checking in federated databases: (1) The problem of constraint checking in a federated database environment is clearly formulated. (2) A family of protocols for constraint checking is presented. (3) The differences across protocols in the family are analyzed with respect to system requirements, properties guaranteed by the protocols, and processing and communication costs. Thus, our work yields a suite of options from which a protocol can be chosen to suit the system capabilities and integrity requirements of a particular federated database environment

    Integrity Constraint Checking in Federated Databases

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    A federated database is comprised of multiple interconnected databases that cooperate in an autonomous fashion. Global integrity constraints are very useful in federated databases, but the lack of global queries, global transaction mechanisms, and global concurrency control renders traditional constraint management techniques inapplicable. The paper presents a threefold contribution to integrity constraint checking in federated databases: (1) the problem of constraint checking in a federated database environment is clearly formulated; (2) a family of cooperative protocols for constraint checking is presented; (3) the differences across protocols in the family are analyzed with respect to system requirements, properties guaranteed, and costs involved. Thus, we provide a suite of options with protocols for various environments with specific system capabilities and integrity requirement

    HELIN Federated Search Task Force Final Report

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    Final report of the HELIN Federated Search Task Force, a group appointed by the HELIN Reference Committee at the request of the HELIN Directors to investigate and report on available federated search engines, which allow users simultaneously to search multiple databases. The task force was not asked to recommend a specific one for licensing by HELIN member libraries and did not do so

    E-infrastructures fostering multi-centre collaborative research into the intensive care management of patients with brain injury

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    Clinical research is becoming ever more collaborative with multi-centre trials now a common practice. With this in mind, never has it been more important to have secure access to data and, in so doing, tackle the challenges of inter-organisational data access and usage. This is especially the case for research conducted within the brain injury domain due to the complicated multi-trauma nature of the disease with its associated complex collation of time-series data of varying resolution and quality. It is now widely accepted that advances in treatment within this group of patients will only be delivered if the technical infrastructures underpinning the collection and validation of multi-centre research data for clinical trials is improved. In recognition of this need, IT-based multi-centre e-Infrastructures such as the Brain Monitoring with Information Technology group (BrainIT - www.brainit.org) and Cooperative Study on Brain Injury Depolarisations (COSBID - www.cosbid.de) have been formed. A serious impediment to the effective implementation of these networks is access to the know-how and experience needed to install, deploy and manage security-oriented middleware systems that provide secure access to distributed hospital based datasets and especially the linkage of these data sets across sites. The recently funded EU framework VII ICT project Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AVERT-IT) is focused upon tackling these challenges. This chapter describes the problems inherent to data collection within the brain injury medical domain, the current IT-based solutions designed to address these problems and how they perform in practice. We outline how the authors have collaborated towards developing Grid solutions to address the major technical issues. Towards this end we describe a prototype solution which ultimately formed the basis for the AVERT-IT project. We describe the design of the underlying Grid infrastructure for AVERT-IT and how it will be used to produce novel approaches to data collection, data validation and clinical trial design is also presented
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