IDAH Speaker Series
Permanent link for this collectionhttps://hdl.handle.net/2022/21650
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Browsing IDAH Speaker Series by Author "Chambliss, Julian"
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Item Mapping Comic Book Imaginaries: Exploring the Landscape of Comic Practice(2020-03-11) Chambliss, JulianWhat is the narrative of comic book history in the United States? For some comic scholars, a canon defined by themes such as trauma, memory, and autobiography defines the use way that comics provide particular insight on popular culture. Whatever these debates about comic canon, the form offers an important opportunity. Comic history is also urban history. Comics have played a central role in shaping our collective understanding of urban life. As visual narrative informed by questions of community, consumption, and identity, the comic medium offers an opportunity to think deeply about how the perception and the reality of urban life evolve through comic pages. In this presentation, Julian Chambliss will discuss the potential benefits offered by Collection as Data project developed by a Michigan State University workgroup using Michigan State University Library (MSUL) library metadata. What narratives of comics and community does such a dataset offer to scholars? How can these narratives engage students and scholars to create a greater understanding of comics and culture in the United States? This talk will highlight some potential pathways offered by comic book cities as windows on a wider urban imaginary in the United States.Item Visualizing Comic Book City Data(2020-03-12) Chambliss, JulianIn this workshop, participants will examine a set of visualizations created by a team of faculty, librarians and academic specialists at Michigan State University. Using Michigan State University Library (MSUL) library data, this group can be utilized to explore questions of community and identity in comics culture. Utilizing the MSUL dataset, we will use Flourish to create visualizations that shed light on the patterns linked to comic publishing in the United States. Participants will leave the workshop with a better understanding of how to prepare data, model it in Flourish, and how to access pre-existing datasets here and elsewhere that work with Flourish.