This chapter explores a code/art method to data visualization using a case study of the project Aperveillance: Watching with Open Data. The generative nature of coding affords a method for creating artistic visualizations that go beyond more traditional charts and graphs. What are the possibilities for leveraging the iterative nature of code in order to create visualizations that focus more on exploration than analysis and offer the chance to raise new questions? Whereas a more traditional approach to data visualization would seek to answer questions or create clearer explanations through the process of visualization, code/art visualizations instead aim to provoke further questions, such as those about the societal tensions between surveillance and privacy in the case study. In addition to explicating the underlying Digital Humanities methods associated with such a practice, this chapter offers a step-by-step guide showing how the Aperveillance project was created using the p5.js programming language.
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Sylvia IV, J.J. (2018). Code/Art Approaches to Data Visualization. In: levenberg, l., Neilson, T., Rheams, D. (eds) Research Methods for the Digital Humanities. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-96713-4_12
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