ArticleJournal of biomedical semantics2015
Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.
Article in Journal of biomedical semantics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Metaverse technology tree: a holistic view.Frontiers in artificial intelligence · 2025Pooled it
- Immune biomarkers, profiles, and responses: a vaccine ontology perspective.Journal of biomedical semantics · 2026Article
- VO: The Vaccine Ontology.Scientific data · 2026Article
- The Ontology of Adverse Events in 2025.Scientific data · 2026Article
- Directory of Public Datasets for Youth Mental Health to Enhance Research Through Data, Accessibility, and Artificial Intelligence: Scoping Review.JMIR mental health · 2025Article
- VO: The Vaccine Ontology.bioRxiv : the preprint server for biology · 2025Article
- Mapping and Harmonization of CVX vaccine terms to the Vaccine Ontology.bioRxiv : the preprint server for biology · 2025Article
- Systematic collection, annotation, and pattern analysis of viral vaccines in the VIOLIN vaccine knowledgebase.Frontiers in cellular and infection microbiology · 2025Article
- Active Learning Pipeline to Identify Candidate Terms for a CDSS Ontology.Studies in health technology and informatics · 2024Article
- Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.Journal of biomedical semantics · 2024Article
- Ontological representation, modeling, and analysis of parasite vaccines.Journal of biomedical semantics · 2024Article
- CanVaxKB: a web-based cancer vaccine knowledgebase.NAR cancer · 2024Article
- Article
- A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.Journal of biomedical semantics · 2022Article
- ICEO, a biological ontology for representing and analyzing bacterial integrative and conjugative elements.Scientific data · 2022Article
- Ten simple rules for making a vocabulary FAIR.PLoS computational biology · 2021Article
- Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection.Scientific data · 2021Article
- TCDO: A Community-Based Ontology for Integrative Representation and Analysis of Traditional Chinese Drugs and Their Properties.Evidence-based complementary and alternative medicine : eCAM · 2021Article
- Combining lexical and context features for automatic ontology extension.Journal of biomedical semantics · 2020Article
- OHMI: the ontology of host-microbiome interactions.Journal of biomedical semantics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundIt 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.
resultsInspired 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.
conclusionsWith 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/.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.