Image Wishlist: Context and Images in Commons-Based Peer Production Communities

Abstract

One promise of commons-based peer production systems is that they provide content (e.g., text, images, sounds, lines of code) for anyone to use, edit, and distribute. However, when some kinds of content are stripped of context and made available for reuse, there are several knock-on effects. In this paper, we discuss how these knock-on effects can complicate the illustration of Wikipedia's encyclopedic articles. We focus on the particularly difficult case of illustrating articles about female anatomy and women's health. Through our analysis, we demonstrate several barriers to illustrating these kinds of articles, including a lack of representative images on Wikimedia Commons, complex issues of consent, and editorial disagreements about the intended audiences for such images. We argue that these barriers are, in part, the unanticipated effects of decontextualization and subsequent recontextualization as images are removed from their original contexts and made available in Wikimedia Commons. Drawing on prior work in language acquisition and archival studies, we critique the design of commons-based peer production systems and suggest ways in which they might be re-designed to account better for the nuances of context. Finally, we raise questions about the costs of recontextualization in peer production systems in general.