Vision is a vital sense that allows people to interact with their surroundings and carry out tasks efficiently while maintaining safety and independence. At least 2.2 billion people globally suffer from blindness or vision impairment, of which more than 1 billion cases are avoidable or untreated because they lack access to eye care services. In ophthalmology, there are numerous challenges in knowledge organization and management, mainly due to the complexity of eye diseases. Ontologies are used as excellent tools for organizing and managing complicated information due to their structured representations of domain knowledge and to make data more findable, accessible, interoperable, and reusable. We have developed an ontology, that is, Eye Disease Ontology (EDO), for the most common eye diseases as a resource that helps in data extraction and analysis for the general public and medical professionals. EDO is a comprehensive and systematic knowledge representation system that categorizes and organizes information about commonly occurring eye diseases such as cataracts, glaucoma, age-related macular degeneration, etc, and connects it to vital details such as symptoms, causes, risk factors, diagnostic tests, and treatment options. The significant metrics of EDO include 566 classes, 16 object properties, 12 data properties, and 119 instances. In this study, the ontology of eye diseases has the potential to improve clinical diagnosis, advance research, and enrich medical education, while improving patient care. This ontology was created using the NeOn technique in the Protégé/OWL environment. Several competency questions were created to meet the demands of various stakeholders, and the ontology was validated using SPARQL queries, the Hermit Reasoner, and the OOPS Pitfalls Scanner. In addition, we develop comprehensive documentation for EDO to promote reuse and emphasise the importance of reuse in future applications.