Documents such as presentations, instruction manuals, and research papers are disseminated using various file formats, many of which barely support the incorporation of interactive content. To address this lack of interactivity, we present Chameleon, a system-wide tool that combines computer vision algorithms used for image identification with an open database format to allow for the layering of dynamic content. Using Chameleon, static documents can be easily upgraded by layering user-generated interactive content on top of static images, all while preserving the original static document format and without modifying existing applications. We describe the development of Chameleon, including the design and evaluation of vision-based image replacement algorithms, the new document-creation pipeline as well as a user study evaluating Chameleon.
https://doi.org/10.1145/3313831.3376559
Research focusing on how collaborative writing takes place across multiple applications and devices and over longer projects is sparse. We respond to this gap by presenting the results of a qualitative study of longer-term academic writing projects, showing how co-writers employ multiple tools when working on a common text. We identify three patterns of multi-application collaboration as well as four common types of motivations for transitions between applications. We also extend existing taxonomies of collaborative writing by proposing a categorization of the functions served by the text as object and backbone of the collaboration. Together, these contributions offer a framing for understanding transitions within and across artifact ecologies in work around a common object. Our findings highlight ways in which features like concurrent editing may in fact challenge the collaborative writing process, and we point to opportunities for alternative application models.
Computers are used for various purposes and frequent context switch is inevitable. In this setting, retrieving the documents, files, and web pages that have been used for a task can be a challenge. While modern applications provide a history of recent documents for users to resume work, this is not sufficient to retrieve all the digital resources relevant to a given primary document. The histories currently available — file names, web page titles, or URLs — does not take into account the complex dependencies that exist among resources across applications. To address this problem, we tested the idea of using a visual history of a computer screen to retrieve digital resources within a few days through the development of ScreenTrack. ScreenTrack is software that captures screenshots of a computer at regular intervals. It then generates a time-lapse video from the captured screenshots and lets users retrieve a recently opened document or web page from a screenshot that they recognize from its visuals. Through a controlled user study, it was found that participants were able to retrieve requested information more quickly with ScreenTrack than under the control condition. A follow-up study showed that the participants used ScreenTrack to retrieve previously used resources, in order to resume interrupted tasks.
This paper introduces document theory as a mechanism to analyze intimate platforms as sociotechnical systems. The theory, developed in documentation studies and applied to HCI, focuses on the casting mold or how agents, through particular means and modes, produce documents that govern social relations. We studied the process of creating a profile by identifying and mapping out the fields asked among the ten most popular online dating apps in the US. By looking at dating profiles as documents and their creation as a process of documentation, we argue that the current casting mold of these intimate platforms is designed to extract profit via invisibilization of labor in digital networks leading to the emergence of a constrained rational market agent. Our study illustrates how document theory makes visible the assumptions of technological systems, calling on us to imagine alternatives beyond incremental design changes given broader structural realities of market and power.
Conceptual diagrams are used extensively to understand abstract relationships, explain complex ideas, and solve difficult problems. To illustrate concepts effectively, experts find appropriate visual representations and translate concepts into concrete shapes. This translation step is not supported explicitly by current diagramming tools. This paper investigates how domain experts create conceptual diagrams via semi-structured interviews with 18 participants from diverse backgrounds. Our participants create, adapt, and reuse visual representations using both sketches and digital tools. However, they had trouble using current diagramming tools to transition from sketches and reuse components from earlier diagrams. Our participants also expressed frustration with the slow feedback cycles and barriers to automation of their tools. Based on these results, we suggest four opportunities of diagramming tools exploration support, representation salience, live engagement, and vocabulary correspondence that together enable a natural diagramming experience. Finally, we discuss possibilities to leverage recent research advances to develop natural diagramming tools.