Autogeneration of web content benefits greatly from well defined input, including data types. MetWare uses XML Schema Data Types for this, as mentioned ealier when I briefly mentioned generation of search pages. That example showed the creation of range input on xsd:integer types. The below screenshot shows the different output for xsd:string (input text box) and xsd:boolean:

Now, this example is not really shocking, but MetWare defines additional types, for example an InChI data type:

<simpleType name="inchi">
  <restriction base="string">
    <pattern value="InChI=1/.*"/>
  </restriction>
</simpleType>

This allows me to tweak the HTML output created by the JSF pages to include microformats to support the Sechemtic userscript (see also doi:10.1186/1471-2105-8-487).

Or, to provide a drop down box, listing the allowed values:

<simpleType name="deviceVendor">
  <restriction base="string">
    <enumeration value="BioCrates"/>
    <enumeration value="Bruecker"/>
  </restriction>
</simpleType>

Note the manual adding of peaks at 10 and 100 m/z to get the real peaks somewhere in the middle instead of on the left and right border of the graph.

Meanwhile, the search page is now autogenerated too, and the types of searches allowed (min, max in the picture) again depends on the XML Scheme data type defined in the MetWare SKOS:

Because of being compatible with various Java libraries and tools, we decided some time ago to use Java. We also wanted to start of with a HTML GUI to MetWare, which led us to Java Server Faces. Not being so fond of Tomcat (e.g. use by the NMRShiftDB), I was not sure how that would turn out, but Steffen was rather positive about it. And I like it :)

The source code for this screenshot is rather simple:

<table>
  <tr valign="top">
    <td><br/>Monoisotopic Mass:<br/>
          min=<inputText id="monomassmin" value="#{metidMetaboliteQuery.monoisotopicMassMin}"/><br/>
          max=<inputText id="monomassmax" value="#{metidMetaboliteQuery.monoisotopicMassMax}"/><br/>
        <commandButton value="Search" id="submit" action="#{metidMetaboliteQuery.search}"/>

        <!--  search results -->
        <p><dataTable value="#{metidMetaboliteQuery.results}" var="mbolite">
           <facet name="caption">Search Results...</facet>
           <column>
             <facet name="header"><outputText value="Monoisotopic mass"/></facet>
             <outputText value="#{mbolite.monoisotopicMass}"/>
           </column>
           <column>
             <facet name="header"><outputText value="InChIKey"/></facet>
             <outputText value="#{mbolite.inchikey}"/>
           </column>
         </dataTable></p>
        </td>
    <td width="25%">
      <b><outputText id="tabelName" value="#{metidMetabolite.prefLabel}"/>:</b>
      <br/>
      <outputText id="tabelDef" value="#{metidMetabolite.definition}"/>
    </td>
  </tr>
</table>

Key concept here is that JSF uses Java Beans, which are referred to in the above example with code like #{bean.field} for bean fields, and with #{bean.method}, assuming a bean exists with getField(), setField() and method(). The <h:outputText> stuff is JSF to work out bean details and will create HTML in the output. As really brief intro.

The Metware Beans

It is clear that java beans for Metware would be useful, and this is what I have been working on for the last few weeks. The relevant beans for the above example are automagically created from the SKOS, complemented with extra bits of RDF for the additional details, like field data type, mapping to SQL tables, and an example value. This all works very smoothly (the code to load() and save() into the SQL database is automatically generated too!) as you can see in the above example. The screenshot shows matches from a (local) live SQL metabolomics database. The text on the right side is directly taken from the SKOS.

Now, the bean library allows integration with other tools too, though this cannot be found in our current roadmap. But, for example, I have been thinking about a simple Bioclipse wrapper around these beans. What is on our roadmap involves workflows for metabolomics.