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OpenStreetMap (OSM) is a volunteer-driven, globally distributed organization whose members work to create a common digital map of the world. OSM embraces ideals of open data, and to that end innovates both socially and technically to develop practices and processes for coordinated operation. This paper provides a brief history of OSM and then, through quantitative and qualitative examination of the OSM database and other sites of articulation work, examines organizational growth through the lens of two catastrophes that spurred enormous humanitarian relief responses-the 2010 Haiti Earthquake and the 2013 Typhoon Yolanda. The temporally-and geographically-constrained events scope analysis for what is a rapidly maturing, whole-planet operation. The first disaster identified how OSM could support other organizations responding to the event. However, to achieve this, OSM has had to refine mechanisms of collaboration around map creation, which were tested again in Typhoon Yolanda. The transformation of work between these two events yields insights into the organizational development of large, data-producing online organizations.OpenStreetMap (OSM) sees itself as a global community that creates a common open digital map of the world. OSM is therefore understood to be both a volunteer-driven organization as well as the map it produces for anyone to use: its members work collaboratively to create a highresolution, global cartographic representation of the planet. Computer scientists in the UK who were frustrated by the licensing restrictions placed on government data by the national mapping agency created OSM in 2004 [5]. In the years since OSM has expanded to a global organization with over 1.5 million registered users and local groups active in over 80 countries, stretching far beyond the initial group of London-based collaborators who could meet in person to discuss problems or plan mapping strategies. In tandem with this growth in membership, OSM map data have also grown to serve a wide range of uses, including adoption by government [9]; private sector organizations including Microsoft Bing, Foursquare, and Telenav; and, of most relevance to this paper, humanitarian organizations working on disaster relief and international development [27,29]. OSM has sought to manage this expansion of scale and scope through a series of efforts to attract new members, articulate the work of ever-larger numbers of volunteers, and deliver map data in more accessible and reliable ways to a growing user base.OSM is often called "the Wikipedia of Maps" because it is a volunteer-driven platform where users collaborate to create freely accessible information. The OSM community is segmented into subgroups that self-organize around geographical areas or themes such as mapping wheelchair accessibility or cycling routes. People are motivated to contribute for a variety of reasons but many cite the value of open spatial data as an important factor for their participation [4]. As a geowiki [24], OSM appears to operate similarly on its surface ...

Human computation and crowdsourcing have become hot topics across several application domains. Indeed, some efforts have been directed toward emergency management to find ways to involve the public in disaster response. However, many tasks in disaster response can put the public in harm's way or introduce problems of liability. Furthermore, some human computation tasks are disconnected from the true needs of emergency response. In this paper we discuss the case of an important lost-and-found taskreuniting displaced pets with their owners after a disaster. We argue why this task is a strong candidate for human computation by "digital volunteers." The goal of this paper is to articulate the design decisions and software engineering problems faced in designing and developing a web-based crowdwork environment that supports a lost-and-found matching task. A Lost-and-Found Problem in Disasters: Pet DisplacementDomestic animals represent a large population in American households. A recent national survey indicates that Americans own an estimated 180 million

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