The rise of open platforms and public APIs has enabled more users of customizable software to customize by installing plugins or add-ons that are created and shared by others. Despite the prevalence of online customization sharing, we know little about how and why online customizations are shared. Through interviews with 20 users of four diverse systems who have extensive experience with sharing their customizations, we reveal the concept of customization sharing ecosystems. These ecosystems include multiple components for hosting customizations, discussing, and managing them; the ecosystems are sustained through users acting in a diverse set of roles (e.g., sharers, re-users, reviewers, problem reporters, requesters, helpers, publicizers, and packers). Our interviews also reveal motivations for creating and sharing customizations online which overlap considerably with those in open source software. Our findings highlight tradeoffs and design considerations in these ecosystems.

Organizing personal information by folders or tags has proved to be effective for finding, remembering, and understanding information. However, past studies have shown that the cost of organization can be too high for some users to be worth the effort. Mixed‐initiative approaches attempt to reduce the burden of manual organization by automatically identifying and suggesting organizational units such as folders to users. However, little is known about how such mixed‐initiative approaches influence users' organizational experiences. In this paper, we explore a mixed‐initiative approach that suggests high‐level organizational units to users to facilitate e‐mail organization. In 2 in‐situ experiments with 34 knowledge workers, we study how our mixed‐initiative approach influenced users' experience with organization. We show that our approach made it easier to create organizational units without negatively affecting recall of those units, and led to the creation of units that otherwise would have not been created. Our findings suggest ways computers and people can most effectively work together to organize information.

Many applications provide personalization mechanisms through which users can make changes to adapt a system to better fit their needs or preferences. However, advanced personalization, such as extending system functionality, is often only available to programmers. Building on ideas from end-user programming and personalization literature, we developed an adaptable task management tool that allows advanced personalization using a self-disclosing mechanism and a guided scripting mechanism, ScriPer. We present our design process, its outcome, and the results of a user study (n=24). Participants, even those with no to some background in programming, were able to use ScriPer to perform advanced personalization (in 142 of 144 trials). We also found error patterns differed across programming expertise.

Facilitating the reuse process and enabling unanticipated reuse can improve efficiency of distributed collaboration. However, supporting the reuse process in complex and dynamic contexts, where future use of information is difficult to predict, is challenging. Collaborative analytics exemplifies such a context. We employed distributed cognition theory to design a collaborative visual analytics system, called AnalyticStream, for facilitating reuse of analysis outcomes. In contrast with the commonly used detail-oriented approach to applying distributed cognition, we performed a high level analysis of the design situation and we identified the cognitive processes that could be distributed over people to facilitate their collaboration. We examined some of the ideas derived from the theoretical analysis, by designing a simple reminding process through recommending relevant pieces of analysis, as well as a mechanism for attention management through allowing users greater control over their shared activity streams. A mixed-methods study of AnalyticStream showed that suggesting relevant artefacts facilitated discovering and consequently reusing them, and provided context-relevant awareness of other analysts' activities.