=Paper=
{{Paper
|id=None
|storemode=property
|title=Ontodog: A Web-based Ontology Community View Generator
|pdfUrl=https://ceur-ws.org/Vol-897/poster_13.pdf
|volume=Vol-897
|dblpUrl=https://dblp.org/rec/conf/icbo/ZhengXSH12
}}
==Ontodog: A Web-based Ontology Community View Generator==
https://ceur-ws.org/Vol-897/poster_13.pdf
Ontodog: A Web-based Ontology Community View Generator
Jie Zheng1*, Zuoshuang Xiang2*, Christian J. Stoeckert Jr1, Yongqun He2
1
Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
2 Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI 48109, USA
ABSTRACT source ontology, and reformat the output files using OWL-
Reference ontologies are often very large and complex. When API. Then the RDF/XML format output files are provided
applied to a specific application, generally a subset of one reference
ontology is needed. Moreover, the labels of ontology terms that were to the users for download.
given in the perspective of ontology developers might not be pre- Ontodog provides a user-friendly web form for data inputs.
ferred labels to the end users. Therefore, it is desirable to have a It contains two sections. The first section collects source
community view of a reference ontology that is a subset of the on-
tology including the terms needed for a particular application or ontology information and tagged terms of interest. The
community with user-preferred labels. Ontodog is a web-based sys- tagged terms of interest and user-specified annotations for
tem to support generation of ontology community views. Ontodog the selected terms are provided either in a tab-delimited or
(http://ontodog.hegroup.org/) allows users to provide terms of inter-
est in a source ontology and customized annotation information,
Excel format file. The second section has three parts corre-
such as user-preferred label. With these inputs, Ontodog can extract sponding to three ontology output files. Output file 1 in-
a subset of the source ontology containing all the terms of interest cludes all tagged terms annotated with a user-specified an-
and generate user specified annotations in RDF/XML format (i.e.,
notation property to indicate they are community subset.
OWL files) which can be used to build an ontology community view.
Currently over 100 ontologies including all OBO Foundry ontologies Output file 2 has customized annotations for the terms, gen-
are available in Ontodog to generate views for a specific application erally used for adding user-specified labels. Output file 3 is
or community. We demonstrate the application of Ontodog in gener- the subset of the source ontology including all terms tagged
ating ontology community views using the Ontology for Biomedical
Investigations (OBI) as the source ontology. in the input term file and related terms/axioms to support
proper reasoning. OntoFox SPARQL related term retrieval
1 INTRODUCTION approach [2] is adopted for ontology subset extraction.
Ontodog allows users to generate all or any combination of
Biomedical ontologies have been widely used in various
applications that facilitate biomedical data integration and the ontology output files described above based on their
sharing. With large reference ontologies, use of the entire needs. The OWL import mechanism is used to build differ-
ontology can impact the efficiency of an application (e.g. ent ontology community views using Ontodog output files.
reasoning, semantic similarity computation) when only a
portion of the ontology is needed. Reference ontologies may 3 USE CASE: APPLICATION OF ONTODOG
be developed collaboratively by various communities aim- IN OBI COMMUNITY VIEWS GENERATION
ing to annotate data consistently regardless of specific re- The Functional Genomics Data (FGED) Society
search areas or technologies. For example, the Ontology for (http://www.fged.org/) supported the migration of the
Biomedical Investigations (OBI) has been developed by MGED Ontology to OBI for functional genomics data anno-
more than 20 communities [1]. The term labels were agreed tation. Criteria for this move included a simplified set of
upon by consensus and generally chosen for ontological terms with (molecular) biologist-community friendly labels.
clarity. Consequently, they may not be the preferred labels Ontodog was used to generate the OBI FGED view
for a particular community or application users. For ontol-
(http://bioportal.bioontology.org/ontologies/1123) for this
ogy users, it is desirable to have their own preferred labels
purpose. 2279 classes identified as relevant for this commu-
in a customized view. We developed Ontodog, a web-based
nity were extracted from OBI (3501 classes).
tool, to address these needs and generate ontology commu-
nity views automatically without need for programming
skills and requiring minimal ontology knowledge. ACKNOWLEDGEMENTS
This research is supported by NIH grants R01AI081062,
2 FEATURES AND USAGE P41HG003619, and R01GM93132.
The Ontodog processes input data using PHP, issues
SPARQL queries against an RDF triple store, e.g., the de- REFERENCES
fault SPARQL endpoint hosted by the He group 1. Brinkman RR, et al (2010) Modeling biomedical experimental proc-
(http://sparql.hegroup.org/sparql), to validate whether terms esses with OBI. J. Biomed. Semantics. 1(Suppl. 1), S7.
exist in the source ontology or retrieve terms from the 2. Xiang Z, et al (2010) OntoFox: web-based support for ontology re-
use. BMC Res Notes. 3:175.
*
Contribute equivalently
1