Evidence map›Paper›PMID 42179940›Full record

ArticleProceedings. IEEE International Conference on Semantic Computing2026

Hootation: A GUI and API library for ontology validation and verbalization.

Muhammad Amith, Xubing Hao, Warren Manuel, Manqi Li, Shun Rao, Kirk Roberts, Hua Xu, Yang Gong, Frank Manion, Cui Tao and 1 more

Abstract read
In one paragraph

Article in Proceedings. IEEE International Conference on Semantic Computing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Muhammad AmithDepartment of Biostatistics and Data Science, Department of Internal Medicine, The University of Texas Medical Branch, Galveston, USA.
Xubing HaoDepartment of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, USA.
Warren ManuelMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, USA.
Manqi LiSchool of Public Health, The University of Texas Health Science Center at Houston, Houston, USA.
Shun RaoDepartment of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, USA.
Kirk RobertsMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, USA.
Hua XuDepartment of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, USA.
Yang GongMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, USA.
Frank ManionVice President for Organizational Transformation, IMO Health, Rosemont, USA.
Cui TaoDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Jacksonville, USA.
Licong CuiMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, USA.

Funding

ACCELERATE-BASSO: Coordinating Center for Accelerating Behavioral and Social Science through OntologyU24AG088019 · NIA · UNIVERSITY OF FLORIDA · PI Jiang Bian, Mark A Musen · 2024 to 2026
$2.3M
Standardizing and Harmonizing Behavioral and Social Science Research Factors in Alzheimer's Disease through Ontology-Based ApproachesU01AG088076 · NIA · MAYO CLINIC JACKSONVILLE · PI Jiang Bian, Cui Tao · 2024 to 2026
$2.3M
Trustworthy and High-Performance Question Answering for Electronic Health RecordsR01LM014508 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Kirk Edward Roberts · 2024 to 2026
$1.1M
Transforming motivational interviewing into a computable model for automated patient diabetic counseling.R21DK134815 · NIDDK · UNIVERSITY OF TEXAS MED BR GALVESTON · PI MUHAMMAD FAHEEM AMITH · 2024 to 2026
$621k
NIA NIH HHS U01 AG088076NIA NIH HHS U24 AG088019NIDDK NIH HHS R21 DK134815NLM NIH HHS R01 LM014508
6 · The paper itself

Abstract

Ontology verbalization refers to the process of translating formal axioms into natural language expressions. The primary objective is to facilitate the review and validation of ontology content by subject matter experts without requiring extensive technical expertise. While previous approaches based on templates or controlled grammar have been effective, they often face limitations in scalability, fluency, and adaptability. To address these issues, we developed Hootation, an open-source software system that supports ontology verbalization through both a graphical user interface and an API library. The tool implements rule-based translation of OWL2 axioms and further incorporates optional Large Language Model (LLM) components for refinement and fact-checking. Hootation allows users to export results for review in common formats such as CSV and Excel. We conducted a usability evaluation using the System Usability Scale (SUS) and achieved an average score of 78.89 (SD = 10.39), which reflects strong ratings and good usability. A one-sample

Indexed as

Large Language ModelsNatural language processingNLGOntologyOntology Quality AuditingSoftwareUsability

Identifiers

PMID42179940
PMCPMC13191566

What OpenQuestion holds

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Registered trials

None linked

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.