# Representing Human Anatomy for Computation and Communication: Synergistic Development of an Anatomical Ontology and Semantically-Augmented Anatomical Graphics

> **NIH NIH R01** · UNIVERSITY OF KENTUCKY · 2024 · $360,113

## Abstract

Project summary
Ontologies represent a domain of knowledge in a form that can be used by both computers and
people. Biomedical ontologies provide standardized representations of knowledge that underlie modern
biomedical research and serve as knowledge bases for enabling intelligent software applications. The
Foundational Model of Anatomy (FMA) is an ontology of human anatomy and has a rich history as one of
the first biomedical ontologies. After 20 years of development, two issues that affect the ability of the
FMA to continue to serve as a source for standardized, computable knowledge of human anatomy have
become apparent: First, variation in modeling schemes and inter-author variation have introduced
inconsistencies, such that similar structures within the body are represented in slightly different ways.
Second, ontologies rely on textual and logical representations, yet visual representations are often more
effective for communicating about anatomy. These issues highlight the need for a next-generation
resource for human anatomy that is optimized for use by both computers and people.
 In this project, we will undertake synergistic development of an ontology of human anatomy and
standardized visual representations of human anatomy. Aim 1: To develop an ontology of human
anatomy suitable for computational reasoning that will serve as a knowledgebase for the next generation
of medical information systems, we will create the Foundational Model of Human Anatomy (FMHA) as a
derivative of the FMA. Aim 2: To provide standardized visual representations of human anatomy for use
in information systems, we will develop libraries of composable graphics depicting canonical anatomy
that will be augmented with computer-readable semantics. Aim 3: To demonstrate use of the FMHA and
standardized graphics to address real-world needs in research, education, and clinical contexts, we will
expand our graphic libraries beyond depictions of canonical anatomy and develop two web applications.
Aim 4: To demonstrate how developers can leverage the FMHA and graphics in their own web
applications, we will develop a web application for graphically-driven exploration of the Disease
Ontology.
 By developing the FMHA and anatomical graphics libraries as highly-curated resources, they will
serve as trustworthy knowledge sources for biomedical applications in data science. By integrating text-
based and visual representations of anatomy, we will help to ensure that researchers accurately
annotate the anatomical content of datasets and models using FMHA classes, thereby helping to
preserve the integrity of integrated datasets and models.
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## Key facts

- **NIH application ID:** 10933393
- **Project number:** 5R01GM149620-02
- **Recipient organization:** UNIVERSITY OF KENTUCKY
- **Principal Investigator:** Melissa Clarkson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $360,113
- **Award type:** 5
- **Project period:** 2023-09-25 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10933393

## Citation

> US National Institutes of Health, RePORTER application 10933393, Representing Human Anatomy for Computation and Communication: Synergistic Development of an Anatomical Ontology and Semantically-Augmented Anatomical Graphics (5R01GM149620-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10933393. Licensed CC0.

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