West Virginia University
This paper presents visualizations of a large dataset containing images and metadata of nonhuman animals. Three camera traps were placed in the foothills of the Appalachian Mountains. Animals move past the camera, motion sensors trigger the taking of a digital picture and store EXIF metadata such as time and date, temperature, and moon phase. This project employs ExifTtool to manipulate image metadata, spreadsheets, Photoshop for batch resizing, and Image J and the ImagePlot macro for visualizing curated datasets. Thousands of deer, turkey, coyotes, bobcats, rabbits, raccoons, possums, and bird species were captured on camera. These individual species are tagged in datasets and their presence can be visualized using combinations of metadata. Drawing on theorists such as Iovino and Opperman, the data visualizations of animals suggest that they are not just an agential force, operating as actors amidst a multitude of others, but a narrator telling a story of the land.
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Hosted at Carleton University, Université d'Ottawa (University of Ottawa)
Ottawa, Ontario, Canada
July 20, 2020 - July 25, 2020
475 works by 1078 authors indexed
Conference cancelled due to coronavirus. Online conference held at https://hcommons.org/groups/dh2020/. Data for this conference were initially prepared and cleaned by May Ning.
Conference website: https://dh2020.adho.org/
Series: ADHO (15)