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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.


Overview of TermGenie Components and Workflow. (1) Retrieve existing templates for user selection; (2) Term generation processing and validation; (2a) Generate textual data and OWL axioms; (2b) Use reasoning to check for existing classes and new or changed relations; (3) Review of generated classes by the user in the web interface; (4) After review, assign permanent identifiers to the new classes; (5) Add the new classes into the queue for review; (6) Senior ontology developers review the classes: accept, modify, obsolete; (7) Commit the changes to the ontology; (8) Send confirmation e-mail to the user.
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Fig2: Overview of TermGenie Components and Workflow. (1) Retrieve existing templates for user selection; (2) Term generation processing and validation; (2a) Generate textual data and OWL axioms; (2b) Use reasoning to check for existing classes and new or changed relations; (3) Review of generated classes by the user in the web interface; (4) After review, assign permanent identifiers to the new classes; (5) Add the new classes into the queue for review; (6) Senior ontology developers review the classes: accept, modify, obsolete; (7) Commit the changes to the ontology; (8) Send confirmation e-mail to the user.

Mentions: The TermGenie application is based on client-server architecture. The web client uses two JavaScript libraries (jQuery [5] and jQuery UI [6]) to implement the user interface in the web browser. The server is written in Java and accepts JSON messages in AJAX RPC calls from the client via a Java servlet listener. Figure 2 illustrates the required TermGenie components and the general workflow for ontology class generation.Figure 2


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)

Overview of TermGenie Components and Workflow. (1) Retrieve existing templates for user selection; (2) Term generation processing and validation; (2a) Generate textual data and OWL axioms; (2b) Use reasoning to check for existing classes and new or changed relations; (3) Review of generated classes by the user in the web interface; (4) After review, assign permanent identifiers to the new classes; (5) Add the new classes into the queue for review; (6) Senior ontology developers review the classes: accept, modify, obsolete; (7) Commit the changes to the ontology; (8) Send confirmation e-mail to the user.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig2: Overview of TermGenie Components and Workflow. (1) Retrieve existing templates for user selection; (2) Term generation processing and validation; (2a) Generate textual data and OWL axioms; (2b) Use reasoning to check for existing classes and new or changed relations; (3) Review of generated classes by the user in the web interface; (4) After review, assign permanent identifiers to the new classes; (5) Add the new classes into the queue for review; (6) Senior ontology developers review the classes: accept, modify, obsolete; (7) Commit the changes to the ontology; (8) Send confirmation e-mail to the user.
Mentions: The TermGenie application is based on client-server architecture. The web client uses two JavaScript libraries (jQuery [5] and jQuery UI [6]) to implement the user interface in the web browser. The server is written in Java and accepts JSON messages in AJAX RPC calls from the client via a Java servlet listener. Figure 2 illustrates the required TermGenie components and the general workflow for ontology class generation.Figure 2

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.