The large ecosystem of observations generated by major space telescope missions can be remotely analyzed using interoperable virtual observatory technologies. In this context of astronomical big data analysis, sonification has the potential of adding a complementary dimension to visualization, enhancing the accessibility of the archives, and offering an alternative strategy to be used when overlapping issues are found in purely graphical representations. This article presents a collection of sonification and musification prototypes that explore the case studies of the MILES and STELIB stellar libraries from the Spanish Virtual Observatory and the Kepler and TESS light curve databases from the Space Telescope Science Institute archive. Using automation and deep learning algorithms, it offers a "palette" of resources that could be used in future developments oriented toward an auditory virtual observatory proposal. The work includes a user study with quantitative and qualitative feedback from specialized and nonspecialized users analyzing the use of sine waves and musical instrument mappings for revealing overlapped lines in galaxy transmission spectra, confirming the need for training and prior knowledge for the correct interpretation of accurate sonifications, and providing potential guidelines to inspire future designs of widely accepted auditory representations for outreach purposes.
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