Fernanda Viegas, Marin Wattenberg, and Kushal Dave describe a visualization system they have built called history flow that they use to visualize changes made to Wikipedia articles. The authors suggest that their papers makes three distinct contributions: * History flow itself which is able to reveal editing patterns in Wikipedia and provide context for editors. * Several examples of collaboration patterns that become visible using the visualization tool and contribute to the literature on Wikipedia. * Implications of these patterns for design and governance of online social spaces. The paper is largely an examination of Wikipedia and the early parts of the paper give background into the sites. It uses shortcomings in the design of the Wikipedia to motivate the history flow visualization which essentially depicts articles, over time, with colors representing authors who contributed text in question. Examples can be seen online at the IBM History Flow website. The interface is particularly good at representing major deletions and insertions. The authors use a lightweight statistically analysis to reveal patterns of editing on Wikipedia (which at the time, were not widely studied). In particular, they show vandalism including mass-deletion, the creation of phony redirects, and addition of idiosyncratic copy and show that it rarely stays on the site for more than few minutes before being removed. They also show a zig-zag patten that represents negotiation of content, often in the form of edit wars. They also attempt to provide some basic data on the stability of Wikipedia and the growth of articles on average. They suggest something that is now taken for granted by researchers of wikis: that studying Wikipedia may have important implications for other types of work. #### Theoretical and practical relevance: The paper is important more for its path-breaking work on Wikipedia -- now with its track at CHI, than for the history flow visualization which has not, for the most part, been widely deployed outside Wikipedia but which seems to hold promise in a variety of other contexts. The paper has been cited more than 400 times, mostly in the academic literature on Wikipedia. This paper is a finalist for the Wikimedia France Research Award.