26,916 research outputs found

    Bioinformatics service reconciliation by heterogeneous schema transformation

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    This paper focuses on the problem of bioinformatics service reconciliation in a generic and scalable manner so as to enhance interoperability in a highly evolving field. Using XML as a common representation format, but also supporting existing flat-file representation formats, we propose an approach for the scalable semi-automatic reconciliation of services, possibly invoked from within a scientific workflows tool. Service reconciliation may use the AutoMed heterogeneous data integration system as an intermediary service, or may use AutoMed to produce services that mediate between services. We discuss the application of our approach for the reconciliation of services in an example bioinformatics workflow. The main contribution of this research is an architecture for the scalable reconciliation of bioinformatics services

    Supporting Change-Aware Semantic Web Services

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    The Semantic Web is not only evolving into a provider of structured meaningful content and knowledge representation, but also into a provider of services. While most of these services support external users of the SW, we focus on a vital service within the SW – change management and adaptation. Change is a ubiquitous feature of the SW. In this paper, we propose a service architecture that embraces and utilises change to provide higher quality services. We introduce pilot implementations of two supporting services within this architecture

    Building Hyper View web sites

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    In this report a framework for building “virtual” web sites using the HyperView system is presented. Virtual web sites are web sites that offer information extracted and integrated from other web sites on the fly. The HyperView system already supports the demand-driven integration of information from different semistructured information sources into a graph database. The problem we are dealing with here is to query the database and generate HTML pages from the results as a response to HTTP requests received from the user. The returned HTML pages should hide the aspects of data extraction and integration and should give the user the impression of a single, coherent web site. We show first how HyperViews comprised of graph-transformation rules can be defined that generate HTML pages from the database. This way web sites for individual application schemata can be designed. In the second part we present a generic rule set that defines a web interface for HyperView graph databases with arbitrary schemata. This generic web interface can be customized for the particular application by annotating the database schema and chosing appropriate styles. The work presented in this report completes the HyperView approach in the sense that it closes the circle of extracting and integrating information from the web by again publishing the integrated data on the web. Our approach applies as well to the integration and generation of XML documents on the web

    Mapping Large Scale Research Metadata to Linked Data: A Performance Comparison of HBase, CSV and XML

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    OpenAIRE, the Open Access Infrastructure for Research in Europe, comprises a database of all EC FP7 and H2020 funded research projects, including metadata of their results (publications and datasets). These data are stored in an HBase NoSQL database, post-processed, and exposed as HTML for human consumption, and as XML through a web service interface. As an intermediate format to facilitate statistical computations, CSV is generated internally. To interlink the OpenAIRE data with related data on the Web, we aim at exporting them as Linked Open Data (LOD). The LOD export is required to integrate into the overall data processing workflow, where derived data are regenerated from the base data every day. We thus faced the challenge of identifying the best-performing conversion approach.We evaluated the performances of creating LOD by a MapReduce job on top of HBase, by mapping the intermediate CSV files, and by mapping the XML output.Comment: Accepted in 0th Metadata and Semantics Research Conferenc
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