Researchers from the Department of Knowledge Technologies (E8) and the Computer Systems Department (E7) at JSI recently published a paper entitled OPTION: Optimization algorithm benchmarking ontology in the top-tier journal in Computer Science (IEEE Transactions on Evolutionary Computation, JCR IF = 16.4). The work presented is a collaboration with external partners from Sorbonne University, France, and Leiden University, the Netherlands. The focus of the paper is on the development of an ontology that enables semantic annotation of the core entities involved in the process of benchmarking optimization algorithms (based on evolutionary computation), which allows for a systematic way of sharing and reusing huge amounts of benchmarking data. The development of the OPTION ontology is a step forward in improving the reusability and interoperability of benchmarking data in the domain of optimization. It follows the principles of and contributes to the practice of Open Science.