7,921 research outputs found

    Automated syntactic mediation for Web service integration

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    As the Web Services and Grid community adopt Semantic Web technology, we observe a shift towards higher-level workflow composition and service discovery practices. While this provides excellent functionality to non-expert users, more sophisticated middleware is required to hide the details of service invocation and service integration. An investigation of a common Bioinformatics use case reveals that the execution of high-level workflow designs requires additional processing to harmonise syntactically incompatible service interfaces. In this paper, we present an architecture to support the automatic reconciliation of data formats in such Web Service worklflows. The mediation of data is driven by ontologies that encapsulate the information contained in heterogeneous data structures supplying a common, conceptual data representation. Data conversion is carried out by a Configurable Mediator component, consuming mappings between \xml schemas and \owl ontologies. We describe our system and give examples of our mapping language against the background of a Bioinformatics use case

    Huddl: the Hydrographic Universal Data Description Language

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    Since many of the attempts to introduce a universal hydrographic data format have failed or have been only partially successful, a different approach is proposed. Our solution is the Hydrographic Universal Data Description Language (HUDDL), a descriptive XML-based language that permits the creation of a standardized description of (past, present, and future) data formats, and allows for applications like HUDDLER, a compiler that automatically creates drivers for data access and manipulation. HUDDL also represents a powerful solution for archiving data along with their structural description, as well as for cataloguing existing format specifications and their version control. HUDDL is intended to be an open, community-led initiative to simplify the issues involved in hydrographic data access

    Shingle 2.0: generalising self-consistent and automated domain discretisation for multi-scale geophysical models

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    The approaches taken to describe and develop spatial discretisations of the domains required for geophysical simulation models are commonly ad hoc, model or application specific and under-documented. This is particularly acute for simulation models that are flexible in their use of multi-scale, anisotropic, fully unstructured meshes where a relatively large number of heterogeneous parameters are required to constrain their full description. As a consequence, it can be difficult to reproduce simulations, ensure a provenance in model data handling and initialisation, and a challenge to conduct model intercomparisons rigorously. This paper takes a novel approach to spatial discretisation, considering it much like a numerical simulation model problem of its own. It introduces a generalised, extensible, self-documenting approach to carefully describe, and necessarily fully, the constraints over the heterogeneous parameter space that determine how a domain is spatially discretised. This additionally provides a method to accurately record these constraints, using high-level natural language based abstractions, that enables full accounts of provenance, sharing and distribution. Together with this description, a generalised consistent approach to unstructured mesh generation for geophysical models is developed, that is automated, robust and repeatable, quick-to-draft, rigorously verified and consistent to the source data throughout. This interprets the description above to execute a self-consistent spatial discretisation process, which is automatically validated to expected discrete characteristics and metrics.Comment: 18 pages, 10 figures, 1 table. Submitted for publication and under revie

    Web and Semantic Web Query Languages

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    A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

    Description of the CUDF Format

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    This document contains several related specifications, together they describe the document formats related to the solver competition which will be organized by Mancoosi. In particular, this document describes: - DUDF (Distribution Upgradeability Description Format), the document format to be used to submit upgrade problem instances from user machines to a (distribution-specific) database of upgrade problems; - CUDF (Common Upgradeability Description Format), the document format used to encode upgrade problems, abstracting over distribution-specific details. Solvers taking part in the competition will be fed with input in CUDF format

    RDF Querying

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    Reactive Web systems, Web services, and Web-based publish/ subscribe systems communicate events as XML messages, and in many cases require composite event detection: it is not sufficient to react to single event messages, but events have to be considered in relation to other events that are received over time. Emphasizing language design and formal semantics, we describe the rule-based query language XChangeEQ for detecting composite events. XChangeEQ is designed to completely cover and integrate the four complementary querying dimensions: event data, event composition, temporal relationships, and event accumulation. Semantics are provided as model and fixpoint theories; while this is an established approach for rule languages, it has not been applied for event queries before
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