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TermGenie - a web-application for pattern-based ontology class generation.

Dietze H, Berardini TZ, Foulger RE, Hill DP, Lomax J, Osumi-Sutherland D, Roncaglia P, Mungall CJ - J Biomed Semantics (2014)

Bottom Line: The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes.All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage.At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

View Article: PubMed Central - PubMed

Affiliation: Genomics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 USA.

ABSTRACT

Background: Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes.

Results: TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes.

Conclusion: TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

No MeSH data available.


Conventional ontology class request workflow. General workflow for ontology class requests using a traditional issue tracker. A simple class request may take several days, for complex cases even longer.
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Fig1: Conventional ontology class request workflow. General workflow for ontology class requests using a traditional issue tracker. A simple class request may take several days, for complex cases even longer.

Mentions: Historically the process used in projects such as the GO Consortium would be for ontology developers to work through a set of requests collected in an issue tracking system, and to manually add them to the ontology, using a specialized Ontology Development Tool (ODT) such as OBO-Edit [1] – see Figure 1. Sometimes the ontology developers apply documented design patterns to guide this process, particularly where collections of classes follow a common structure. For example, most classes in the developmental process portion of the GO follow a consistent lexical form and relational structure as dictated in the GO developers documentation [2]. However, even with this documentation in place, this has still largely been a time-consuming and error-prone manual process, especially where ontology developers need to rearrange to the ontology structure.Figure 1


TermGenie - a web-application for pattern-based ontology class generation.

Dietze H, Berardini TZ, Foulger RE, Hill DP, Lomax J, Osumi-Sutherland D, Roncaglia P, Mungall CJ - J Biomed Semantics (2014)

Conventional ontology class request workflow. General workflow for ontology class requests using a traditional issue tracker. A simple class request may take several days, for complex cases even longer.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4417543&req=5

Fig1: Conventional ontology class request workflow. General workflow for ontology class requests using a traditional issue tracker. A simple class request may take several days, for complex cases even longer.
Mentions: Historically the process used in projects such as the GO Consortium would be for ontology developers to work through a set of requests collected in an issue tracking system, and to manually add them to the ontology, using a specialized Ontology Development Tool (ODT) such as OBO-Edit [1] – see Figure 1. Sometimes the ontology developers apply documented design patterns to guide this process, particularly where collections of classes follow a common structure. For example, most classes in the developmental process portion of the GO follow a consistent lexical form and relational structure as dictated in the GO developers documentation [2]. However, even with this documentation in place, this has still largely been a time-consuming and error-prone manual process, especially where ontology developers need to rearrange to the ontology structure.Figure 1

Bottom Line: The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes.All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage.At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

View Article: PubMed Central - PubMed

Affiliation: Genomics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 USA.

ABSTRACT

Background: Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes.

Results: TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes.

Conclusion: TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

No MeSH data available.