An art installation was on display in the Centre Pompidou National Museum of Modern Art in Paris, where visitors could contribute with their own personal objects, adding keyword descriptions and quantified semantic features such as age or hardness. The data was projected in real-time onto a Self-Organizing Map (SOM) which was shown in the gallery. In this paper we analyze the same data by extracting visual features from the images and organize the image collection with multiple SOMs. We show how this mapping facilitates the emergence of semantic associations between visual, textual and metadata modalities by studying the distributions of the different feature vectors on the SOMs.