Standardized data organization is crucial in scientific research as it facilitates effective sharing, collaboration, and reproducibility. In neuroscience, the Brain Imaging Data Structure (BIDS) has emerged as a leading standard for organizing neuroimaging and behavioral data. However, a significant gap remains for audio and musical data. This thesis proposes an extension to BIDS referred to as BIDS-Audio to accommodate the unique requirements of auditory and musical stimuli in neuroscience experiments. By integrating audio files and their associated metadata into the established BIDS framework, the proposed extension aims to streamline data processing, enhance transparency, and enable the development of automated analysis tools. The work presented here includes a comprehensive literature review, a survey of current practices, the design of a flexible folder hierarchy with detailed metadata sidecars, modifications to the BIDS schema and validator, and practical demonstrations by using prototypical datasets.