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    <article-meta>
      <title-group>
        <article-title>Analysis and visualisation of RDF resources in Ondex</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Catherine Canevet</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Artem Lysenko</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Andrea Splendiani</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Matthew Pocock</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Christopher Rawlings</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Centre for Mathematical and Computational Biology, Rothamsted Research</institution>
          ,
          <addr-line>Harpenden</addr-line>
          ,
          <country country="UK">UK</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>School of Computing Science, University of Newcastle</institution>
          ,
          <addr-line>Newcastle</addr-line>
          ,
          <country country="UK">UK</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>An increasing number of biomedical resources provide their information on the Semantic Web and this creates the basis for a distributed knowledge base which has the potential to advance biomedical research [1]. This potential, however, cannot be realised until researchers from the life sciences can interact with information in the Semantic Web. In particular, there is a need for tools that provide data reduction, visualization and interactive analysis capabilities. Ondex is a data integration and visualization platform developed to support Systems Biology Research [2]. At its core is a data model based on two main principles: first, all information can be represented as a graph and, second, all elements of the graph can be annotated with ontologies. This data model is conformant to the Semantic Web framework, in particular to RDF, and therefore Ondex is ideally positioned as a platform that can exploit the semantic web. The Ondex system offers a range of features and analysis methods of potential value to semantic web users, including: - An interactive graph visualization interface (Ondex user client), which provides data reduction and representation methods that leverage the ontological annotation. - A suite of importers from a variety of data sources to Ondex (http://ondex.org/formats.html) - A collection of plug-ins which implement graph analysis, graph transformation and graph-matching functions. - An integration toolkit (Ondex Integrator) which allows users to compose workflows from these modular components - In addition, all importers and plug-ins are available as web-services which can be integrated in other tools, as for instance Taverna [3].</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>In this demo we will show how Ondex can be used to query, analyse and visualize
Semantic Web knowledge bases. In particular we will present real use cases focused,
but not limited to, resources relevant to plant biology.</p>
      <p>We believe that Ondex can be a valid contribution to the adoption of the Semantic
Web in Systems Biology research and in biomedical investigation more generally. We
welcome feedback on our current import/export prototype and suggestions for the
advancement of Ondex for the Semantic Web.</p>
    </sec>
  </body>
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