Collaborations between artists is very frequent in music industry and data analysis can help understand the impact of collaborative projects on artists’ careers. In this paper, we propose an incremental and multimodal visualization to support the exploration of artists’ discography and collabo- rations. Visualization techniques are used here to support the discovery of meaningful patterns and causal relation- ships. Our approach combines meta-data, graphics, inter- active audio, and MIR analysis to explore the data using a Web browser. As a case of study, we explore the data from the WASABI knowledge graph, which describes the discography of more than 77,000 artists, representing over 200,000 albums and two million songs. We designed a web platform that requests metadata of any artist/band, parses the results, and displays the data through a visualization technique that combines stream-graphs, timelines and net- work representation. Audio thumbnailing techniques have been used to summarize an entire album or discography, which is used through a Web Audio augmented player integrated into the visualization to support auditory exploration of data. Advanced in-depth exploration of individual songs is supported through MIR analysis performed and displayed directly in the web browser. We demonstrate the use and feasibility of our method through a series of usage scenarios and validate its usefulness through expert judgment.