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    <journal-meta>
      <journal-title-group>
        <journal-title>Ozgur A, et al. Mining of vaccine-associated IFN- gene
interaction networks using the Vaccine Ontology.
Journal of Biomedical Semantics.</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>Ontorat web server for automatic generation and annotations of new ontology terms Zuoshuang Xiang, Yu Lin, Yongqun He</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Zuoshuang Xiang</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Yu Lin</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Yongqun He</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>University of Michigan Medical School</institution>
          ,
          <addr-line>Ann Arbor</addr-line>
          ,
          <country country="US">USA</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2011</year>
      </pub-date>
      <volume>2</volume>
      <abstract>
        <p>The Web Ontology Language (OWL) has been widely used for ontology development. However, development of a new ontology in OWL is often time consuming and requires specialized knowledge in ontology, OWL, and specific domain science. One frequently observed phenomenon during ontology development is that often we need to create a large number of new ontology terms that follow the same design patterns of logical definitions and axioms. Manual addition of these terms is time consuming, error prone, and often boring. Ontorat is developed to facilitate this process.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Introduction</title>
      <p>Ontorat is developed based on the Ontology
Design Patterns (OCPs) in the field of ontology
engineering. Ontorat uses the class expressions with
variables, which is defined as "OWL class
expressions but allowing variables at positions of
class expressions. The range of a variable can either
be a named class, class expression, or any subtype of
it as produced by the corresponding rule in OWL."
(Noppens and Liebig, 2009). Ontorat offers a
webbased platform for writing up class expressions with
variables with the aim to quickly generate a large
number of new ontology classes or annotate existing
classes in a specific target ontology.</p>
      <p>The development of Ontorat is also inspired by the
Ontology for Biomedical Investigations (OBI) project
QTT (Quick Term Templates) (Rocca-Serra, et al.,
2011). The OBI QTT procedure is based on the
concept of a Quick Term Template (QTT), a template
in a spreadsheet format that can be converted into an
OWL file. The QTT procedure has been implemented
in MappingMaster, a plugin program in the
ProtégéOWL editor. Similar to MappingMaster, Ontorat uses
an Excel or tab-delimited spreadsheet file as input.
Ontorat also relies on the pattern program using the
OWL Manchester Syntax, a new syntax designed for
writing OWL class expressions
(http://www.w3.org/TR/owl2-manchester-syntax/).
Different from MappingMaster, Ontorat is
implemented as a web-based application. The
MappingMaster plugin works in Protege 3.4 but does
not work in Protege 4.x. Ontorat provides a novel
feature of automatic assignment of unique ontology
identifiers. In addition, Ontorat, but not
MappingMaster, can generate annotations for
ontology terms.</p>
    </sec>
    <sec id="sec-2">
      <title>Features and Usage</title>
      <p>Ontorat (http://ontorat.hegroup.org) provides a
userfriendly web form for data input. The Ontorat input
include: (i) a target ontology in OWL format, (ii) the
data file (an Excel file or tab-delimited text file), (iii)
purpose of the new axiom generation, (iv) assignment
of annotations using Manchester OWL Syntax, (v)
assignment of equivalent classes, (vi) assignment of
superclasses, (vii) definitions of ontology terms used
in the above three assignments, (viii) prefix of term
URI, (ix) information for automatically assigning
term IDs, including prefix, number of digits, and start
ID. The Ontorat output is an OWL file. Using the
Protégéontology editor (http://protege.stanford.edu/),
an Ontorat output OWL file can be directly visualized
and imported (or merged) in the target ontology (e.g.,
VO) using the OWL import function.</p>
      <p>As a demonstration, we will demonstrate how
Ontorat is used to facilitate the development of the
Vaccine Ontology (VO) (He, et al, 2009). VO is a
community-based ontology in the domain of vaccine
and vaccination. There are hundreds of licensed
animal vaccines used in the USA. Ontorat is able to
import these animal vaccines and their annotations
into VO efficiently.</p>
      <p>The Ontorat web server provides a robust and
scalable approach for automatically generating new
ontology terms and their annotations. Ontorat
supports efficient ontology enrichment and
expansion. The design patterns can be standardized
and reused, allowing domain experts and data
curators to contribute actively to the ontology
development without knowing the specifics of OWL.
Acknowledgements: This research is supported by a
NIH R01 grant (1R01AI081062).</p>
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