15 research outputs found

    E-BioFlow: Different Perspectives on Scientific Workflows

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    We introduce a new type of workflow design system called\ud e-BioFlow and illustrate it by means of a simple sequence alignment workflow. E-BioFlow, intended to model advanced scientific workflows, enables the user to model a workflow from three different but strongly coupled perspectives: the control flow perspective, the data flow perspective, and the resource perspective. All three perspectives are of\ud equal importance, but workflow designers from different domains prefer different perspectives as entry points for their design, and a single workflow designer may prefer different perspectives in different stages of workflow design. Each perspective provides its own type of information, visualisation and support for validation. Combining these three perspectives in a single application provides a new and flexible way of modelling workflows

    Provenance-based validation of E-science experiments

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    E-Science experiments typically involve many distributed services maintained by different organisations. After an experiment has been executed, it is useful for a scientist to verify that the execution was performed correctly or is compatible with some existing experimental criteria or standards. Scientists may also want to review and verify experiments performed by their colleagues. There are no existing frameworks for validating such experiments in today's e-Science systems. Users therefore have to rely on error checking performed by the services, or adopt other ad hoc methods. This paper introduces a platform-independent framework for validating workflow executions. The validation relies on reasoning over the documented provenance of experiment results and semantic descriptions of services advertised in a registry. This validation process ensures experiments are performed correctly, and thus results generated are meaningful. The framework is tested in a bioinformatics application that performs protein compressibility analysis

    SIMDAT

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    An overview of S-OGSA: A Reference Semantic Grid Architecture

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    The Grid's vision, of sharing diverse resources in a flexible, coordinated and secure manner through dynamic formation and disbanding of virtual communities, strongly depends on metadata. Currently, Grid metadata is generated and used in an ad hoc fashion, much of it buried in the Grid middleware's code libraries and database schemas. This ad hoc expression and use of metadata causes chronic dependency on human intervention during the operation of Grid machinery, leading to systems which are brittle when faced with frequent syntactic changes in resource coordination and sharing protocols. The Semantic Grid is an extension of the Grid in which rich resource metadata is exposed and handled explicitly, and shared and managed via Grid protocols. The layering of an explicit semantic infrastructure over the Grid Infrastructure potentially leads to increased interoperability and greater flexibility. In recent years, several projects have embraced the Semantic Grid vision. However, the Semantic Grid lacks a Reference Architecture or any kind of systematic framework for designing Semantic Grid components or applications. The Open Grid Service Architecture ( OGSA) aims to define a core set of capabilities and behaviours for Grid systems. We propose a Reference Architecture that extends OGSA to support the explicit handling of semantics, and defines the associated knowledge services to support a spectrum of service capabilities. Guided by a set of design principles, Semantic-OGSA ( S-OGSA) defines a model, the capabilities and the mechanisms for the Semantic Grid. We conclude by highlighting the commonalities and differences that the proposed architecture has with respect to other Grid frameworks. (c) 2006 Elsevier B. V. All rights reserved

    Preservation metadata initiatives: practicality, sustainability, and interoperability

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    Estudio cualitativo de la relaciĆ³n de las leyes y la pericia informĆ”tica en el Ecuador

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    Resumen: El presente trabajo analiza cualitativamente las leyes vigentes en el Ecuador relacionadas a los procesos de la pericia informĆ”tica. Para aquello, se estudia los pasos empleados por un perito de la PolicĆ­a Nacional en el desarrollo de los casos de delito informĆ”tico, suscitados en el periodo 2012-2014, que implican la evidencia digital en: disco duros, cuentas de correo electrĆ³nico, redes sociales y motor de base datos. Apartir de los casos analizados, se puede concluir que la ley contempla una mayor cantidad de artĆ­culos relacionados a las bases de datos. Sin embargo, se tendrĆ­a que analizar otros tipos de evidencia digital tales como: documentos de ofimĆ”tica, imĆ”genes digitales, ficheros de registros de actividad, memoria volĆ”til, entre otros.Ā Palabras Clave: Pericia InformĆ”tica, evidencia digital, perito informĆ”tico, CĆ³digo OrgĆ”nico Integral Penal (COIP)

    Automating Experiments Using Semantic Data on a Bioinformatics Grid

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    myGrid assists bioinformaticians in designing and executing in silico experiments using the Gridā€™s resources. In myGrid, much of this experimental design has been encoded as workflows. Workflows must be represented at tiered levels of detail to ensure that they can respond to changes in service availability, be customized to services in different locations, and be shared with others to varying degrees. The authors have developed workflow templates in which classes of services are composed, and a resolution mechanism by which these classes are instantiated. The specification of service classes and their resolution depends on seven kinds of service metadata. Functionally equivalent services vary widely in implementation. The authors describe workflow harmonization in which the workflow is modified to accommodate variations between substituted services. Finally, they examine the role of scientist and automated process in resolution and harmonization and discuss scope for further automation

    The Origin of Data: Enabling the Determination of Provenance in Multi-institutional Scientific Systems through the Documentation of Processes

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    The Oxford English Dictionary defines provenance as (i) the fact of coming from some particular source or quarter; origin, derivation. (ii) the history or pedigree of a work of art, manuscript, rare book, etc.; concr., a record of the ultimate derivation and passage of an item through its various owners. In art, knowing the provenance of an artwork lends weight and authority to it while providing a context for curators and the public to understand and appreciate the workā€™s value. Without such a documented history, the work may be misunderstood, unappreciated, or undervalued. In computer systems, knowing the provenance of digital objects would provide them with greater weight, authority, and context just as it does for works of art. Specifically, if the provenance of digital objects could be determined, then users could understand how documents were produced, how simulation results were generated, and why decisions were made. Provenance is of particular importance in science, where experimental results are reused, reproduced, and verified. However, science is increasingly being done through large-scale collaborations that span multiple institutions, which makes the problem of determining the provenance of scientific results significantly harder. Current approaches to this problem are not designed specifically for multi-institutional scientific systems and their evolution towards greater dynamic and peer-to-peer topologies. Therefore, this thesis advocates a new approach, namely, that through the autonomous creation, scalable recording, and principled organisation of documentation of systemsā€™ processes, the determination of the provenance of results produced by complex multi-institutional scientific systems is enabled. The dissertation makes four contributions to the state of the art. First is the idea that provenance is a query performed over documentation of a systemā€™s past process. Thus, the problem is one of how to collect and collate documentation from multiple distributed sources and organise it in a manner that enables the provenance of a digital object to be determined. Second is an open, generic, shared, principled data model for documentation of processes, which enables its collation so that it provides high-quality evidence that a systemā€™s processes occurred. Once documentation has been created, it is recorded into specialised repositories called provenance stores using a formally specified protocol, which ensures documentation has high-quality characteristics. Furthermore, patterns and techniques are given to permit the distributed deployment of provenance stores. The protocol and patterns are the third contribution. The fourth contribution is a characterisation of the use of documentation of process to answer questions related to the provenance of digital objects and the impact recording has on application performance. Specifically, in the context of a bioinformatics case study, it is shown that six different provenance use cases are answered given an overhead of 13% on experiment run-time. Beyond the case study, the solution has been applied to other applications including fault tolerance in service-oriented systems, aerospace engineering, and organ transplant management
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