We study the structural properties of large scale collaboration in online communities of innovation and the role that position in the community plays in determining knowledge contribution. Contrary to previous research, we argue for a more local perspective when examining online collaboration. We demonstrate that a member's centrality and spanning within his/her local neighborhood is a better predictor of contribution than global centrality and spanning within the whole community. We contribute both theoretically and methodologically to research on large scale collaboration. On the theoretical front, a local view of position implies a more confined and local organization of work in online communities than previously thought. From a methodological perspective, evaluating the local structure of large networks involves radically different algorithms that have only recently become feasible with the increase of processing power.