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Related Experiment Video

Updated: Apr 14, 2026

Dissection of Organizer and Animal Pole Explants from Xenopus laevis Embryos and Assembly of a Cell Adhesion Assay
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OTO: Ontology Term Organizer.

Fengqiong Huang1, James A Macklin2, Hong Cui3

  • 1School of Information Resources and Library Science, University of Arizona, Tucson, USA. huangfq@email.arizona.edu.

BMC Bioinformatics
|April 19, 2015
PubMed
Summary
This summary is machine-generated.

The Ontology Term Organizer (OTO) is a user-friendly, open-source tool that helps domain experts build ontologies by organizing terms and relationships. It facilitates consensus among experts and improves ontology coverage for better knowledge organization.

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Area of Science:

  • Bioinformatics
  • Knowledge Organization

Background:

  • Controlled vocabularies and ontologies are crucial for knowledge organization across domains.
  • Existing ontology construction tools often require specialized knowledge engineering skills, excluding domain experts.
  • Current software rarely addresses differing expert opinions or varied terminology in source literature.

Purpose of the Study:

  • To develop a user-friendly, web-based application for domain experts to construct ontologies.
  • To facilitate consensus-building among multiple domain experts.
  • To enhance the coverage of formal ontologies by organizing domain-specific terms.

Main Methods:

  • The Ontology Term Organizer (OTO) software was developed using Agile principles with iterative feedback.
  • OTO is an open-source, web-based application built in Java.
  • Users organize terms by dragging and dropping them to establish relationships like 'is_a' and 'part_of'.

Main Results:

  • OTO is a user-friendly, consensus-promoting application for organizing domain terms.
  • It supports users with domain knowledge but not necessarily ontology construction expertise.
  • The software allows for the establishment of various term relationships, reflecting source literature and expert consensus.
  • Organized terms can be integrated into formal ontologies, increasing their scope.

Conclusions:

  • OTO has been successfully applied to large-scale datasets, such as botanical literature.
  • User feedback confirms OTO's efficiency and user-friendliness.
  • As open-source software, OTO is adaptable for diverse domain-specific term organization needs.