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Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.

Xiang Z, Zheng J, Lin Y, He Y - J Biomed Semantics (2015)

Bottom Line: The OBI team used Ontorat to add assay and device terms required by ENCODE project.Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology.A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development.

View Article: PubMed Central - PubMed

Affiliation: University of Michigan, Ann Arbor, MI USA.

ABSTRACT

Background: It is time-consuming to build an ontology with many terms and axioms. Thus it is desired to automate the process of ontology development. Ontology Design Patterns (ODPs) provide a reusable solution to solve a recurrent modeling problem in the context of ontology engineering. Because ontology terms often follow specific ODPs, the Ontology for Biomedical Investigations (OBI) developers proposed a Quick Term Templates (QTTs) process targeted at generating new ontology classes following the same pattern, using term templates in a spreadsheet format.

Results: Inspired by the ODPs and QTTs, the Ontorat web application is developed to automatically generate new ontology terms, annotations of terms, and logical axioms based on a specific ODP(s). The inputs of an Ontorat execution include axiom expression settings, an input data file, ID generation settings, and a target ontology (optional). The axiom expression settings can be saved as a predesigned Ontorat setting format text file for reuse. The input data file is generated based on a template file created by a specific ODP (text or Excel format). Ontorat is an efficient tool for ontology expansion. Different use cases are described. For example, Ontorat was applied to automatically generate over 1,000 Japan RIKEN cell line cell terms with both logical axioms and rich annotation axioms in the Cell Line Ontology (CLO). Approximately 800 licensed animal vaccines were represented and annotated in the Vaccine Ontology (VO) by Ontorat. The OBI team used Ontorat to add assay and device terms required by ENCODE project. Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology. A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development.

Conclusions: With ever increasing ontology development and applications, Ontorat provides a timely platform for generating and annotating a large number of ontology terms by following design patterns.

Availability: http://ontorat.hegroup.org/.

No MeSH data available.


The strategy of applying ODPs into ontology term and annotation generation. An ODP is used to guide the generation of axiom settings and a template file (text or Excel format). The template file is populated with specific contents to create an input data file. Based on the axiom assertions and input data file, an OWL output can be generated by a software program to expand a targeted ontology.
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Fig1: The strategy of applying ODPs into ontology term and annotation generation. An ODP is used to guide the generation of axiom settings and a template file (text or Excel format). The template file is populated with specific contents to create an input data file. Based on the axiom assertions and input data file, an OWL output can be generated by a software program to expand a targeted ontology.

Mentions: Based on the ODP concept and the Quick Term Templates (QTT) procedure, we developed an overall strategy of applying these mechanisms to ontology expansion (Figure 1). First, an ODP that covers a set of terms and their relations needs to be identified (Figure 1a). Formal axioms that assert logical relations among ontology terms and annotations of these terms will then be specified based on the ODP (Figure 1b). The ODP will guide the generation of a tab-delimited text or Excel template file which would contain all terms and annotations needed to define targeted terms (Figure 1c). This template file will then be used to populate specific contents (Figure 1d). By combining the axiom settings and the input data file, an OWL format output can be generated (Figure 1e).


Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.

Xiang Z, Zheng J, Lin Y, He Y - J Biomed Semantics (2015)

The strategy of applying ODPs into ontology term and annotation generation. An ODP is used to guide the generation of axiom settings and a template file (text or Excel format). The template file is populated with specific contents to create an input data file. Based on the axiom assertions and input data file, an OWL output can be generated by a software program to expand a targeted ontology.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4362828&req=5

Fig1: The strategy of applying ODPs into ontology term and annotation generation. An ODP is used to guide the generation of axiom settings and a template file (text or Excel format). The template file is populated with specific contents to create an input data file. Based on the axiom assertions and input data file, an OWL output can be generated by a software program to expand a targeted ontology.
Mentions: Based on the ODP concept and the Quick Term Templates (QTT) procedure, we developed an overall strategy of applying these mechanisms to ontology expansion (Figure 1). First, an ODP that covers a set of terms and their relations needs to be identified (Figure 1a). Formal axioms that assert logical relations among ontology terms and annotations of these terms will then be specified based on the ODP (Figure 1b). The ODP will guide the generation of a tab-delimited text or Excel template file which would contain all terms and annotations needed to define targeted terms (Figure 1c). This template file will then be used to populate specific contents (Figure 1d). By combining the axiom settings and the input data file, an OWL format output can be generated (Figure 1e).

Bottom Line: The OBI team used Ontorat to add assay and device terms required by ENCODE project.Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology.A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development.

View Article: PubMed Central - PubMed

Affiliation: University of Michigan, Ann Arbor, MI USA.

ABSTRACT

Background: It is time-consuming to build an ontology with many terms and axioms. Thus it is desired to automate the process of ontology development. Ontology Design Patterns (ODPs) provide a reusable solution to solve a recurrent modeling problem in the context of ontology engineering. Because ontology terms often follow specific ODPs, the Ontology for Biomedical Investigations (OBI) developers proposed a Quick Term Templates (QTTs) process targeted at generating new ontology classes following the same pattern, using term templates in a spreadsheet format.

Results: Inspired by the ODPs and QTTs, the Ontorat web application is developed to automatically generate new ontology terms, annotations of terms, and logical axioms based on a specific ODP(s). The inputs of an Ontorat execution include axiom expression settings, an input data file, ID generation settings, and a target ontology (optional). The axiom expression settings can be saved as a predesigned Ontorat setting format text file for reuse. The input data file is generated based on a template file created by a specific ODP (text or Excel format). Ontorat is an efficient tool for ontology expansion. Different use cases are described. For example, Ontorat was applied to automatically generate over 1,000 Japan RIKEN cell line cell terms with both logical axioms and rich annotation axioms in the Cell Line Ontology (CLO). Approximately 800 licensed animal vaccines were represented and annotated in the Vaccine Ontology (VO) by Ontorat. The OBI team used Ontorat to add assay and device terms required by ENCODE project. Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology. A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development.

Conclusions: With ever increasing ontology development and applications, Ontorat provides a timely platform for generating and annotating a large number of ontology terms by following design patterns.

Availability: http://ontorat.hegroup.org/.

No MeSH data available.