Data Analysis and Visualization for the Humanities and Social Sciences

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This course is designed for students interested in the relationship between how digital objects (with a focus on the historical and cultural) are created and consumed, as well as how novel tools and methods provide opportunities for new types of analysis, research, and dissemination. By introducing you to the basics of digitisation, data analysis, and representation, this course will also explore the theoretical underpinnings, biases, and lacunae of working with data, while teaching you to be more critically reflective of digital tools, processes and products. Ultimately, this course is an introduction to the field of Digital Humanities which explores the impact, opportunities, and affordances of the digitisation of our cultural heritage, providing innovative means to approach traditional fields of expertise. The course will explore digitalisation from three perspectives: Digitisation, Analysis, and Representation. The first half of the course will focus on digitisation, with particular reference to 3D, placing emphasis on the field of computational imaging; a field in computer science that studies the computational extraction of information from digital photographs. You will develop 3D recording skills by completing a mini group project, and reflect on the process in terms of what is gained and lost by representing physical objects within virtual computer interfaces. The second half of the course will focus on text analysis. A mini big data project will provide you with hands-on experience and understanding of the affordances and limitations of text analysis methods. We will explore how the representation of text in more visual formats which are typically removed from its semantic contexts, offers opportunities for both new insights as well as misrepresentation. An overarching goal of the course is to is to help you become more savvy users of digital information: the implications and challenges that methods and technologies pose to conventional research, analysis and publication in the arts, humanities, and social sciences, including issues such as copyright, transparency, authenticity, and bias.