Representing Bionic-Vision Devices in the Neural Electronic Interface Ontology – Abstract Jisoo Seo1,∗ , Alexander D. Diehl1 , Daniel L. Rathbun2 , Gopikrishnan M. Chandrasekharan3 , Callie McGrath4 and William D. Duncan3 1 University at Buffalo, Buffalo, NY 14260, USA 2 Detroit Institute of Ophthalmology, Henry Ford Health, Detroit, MI 48202, USA 3 University of Florida College of Dentistry, Gainesville, FL 32610, USA 4 Independent Researcher, Tacoma, WA 98402, USA Abstract Devices such as retinal and cochlear implants improve the quality of life for those suffering from vision or hearing loss. These devices interface with the central nervous system to enhance (or augment) stimuli from the patient’s external environment. However, there are major obstacles to the effective use of this technology. Standards are lacking for defining the types of devices used for this purpose, the conditions under which these devices should be employed, the assessment of patients’ sensory ability, and the metrics for evaluating the performance of these devices. For example, due to the lack of precise epidemiological data to distinguish between low and ultra- low vision levels, it is difficult to estimate the number of suitable vision loss patients. To address these needs, we are developing the Neural Electronic Interface Ontology (NEIO). NEIO uses ontological principles to address these challenges. Genus-differentia definitions, taxonomic hierarchies, and formal relations precisely define the different kinds of neural-interface devices. Such definitions include device components and functions, and the pathological conditions that these devices address. Where relevant, we reuse classes from other ontologies in order to leverage the expertise of the developers of these ontologies and promote interoperability. For example, we use Uberon to represent the anatomical locations where the devices are implanted. We are using data from bionic-visions.org to create classes to represent the bionic-vision devices, relevant components of these devices, and the organizations that produce them. We are currently adding measures of visual ability. These measures will enable comparisons between outcomes from various sight restoration methods. The comparison classes include bionic-vision devices, gene therapy, stem-cell therapy, and pharmaceuticals. This work forms the foundation of an ontological framework to represent the assessment of visual ability. This framework will, in turn, facilitate the identification of appropriate vision restoration procedures for patients with a variety of eye diseases, thereby optimizing patient outcomes. Finally, although NEIO is currently focused on bionic vision, NEIO aims to provide a semantic framework for representing the domain of neural electronic interface technology in general. Keywords Ontology, Neural-Interface Devices, Bionic Vision, Retina Implant 15th International Conference on Biomedical Ontologies 2024, July 17-19, 2024, Enschede, The Netherlands ∗ Corresponding author. Envelope-Open jisooseo@buffalo.edu (J. Seo); addiehl@buffalo.edu (A. D. Diehl); drathbu2@hfhs.or (D. L. Rathbun); gopikrishnan.mc@gmail.com (G. M. Chandrasekharan); philosophy@calliemcgrath.space (C. McGrath); wdduncan@gmail.com (W. D. Duncan) Orcid 0009-0008-8150-9779 (J. Seo); 0000-0001-9990-8331 (A. D. Diehl); 0000-0001-7387-7944 (D. L. Rathbun); 0009-0006-7251-3026 (G. M. Chandrasekharan); 0009-0005-6233-0827 (C. McGrath); 0000-0001-9625-1899 (W. D. Duncan) © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR ceur-ws.org Workshop ISSN 1613-0073 Proceedings