Abstract Members of cooperative groups can work together more effectively if they develop a shared classification schema, but distributed groups face barriers to doing so. To better understand how classifications and classification practices can emerge and support the work of distributed groups, we review the literature on folksonomies (a kind of shared classification schema) in crowdsourcing projects (one type of distributed work). The review yields three potentially productive tensions associated with the development of folksonomies in crowdsourcing projects. First, projects must establish who has the authority to decide on adopted terminology and with what consequences. Second, there can be tension if people who tag objects have different interests in tagging than those who use the tags to search for content. Finally, projects must decide when to intervene to maintain a balance between a stable vocabulary and the ability of the project to accommodate ongoing changes. We illustrate these tensions by comparing how they are handled in the photo-sharing site Flickr, the story-sharing site Archive of Our Own (AO3), the internet culture classification site Know Your Meme, and the citizen science project Gravity Spy. The comparison suggests guidelines for project managers regarding the identified tensions.

In human-computer interaction (HCI) studies, bias in the gender representation of participants can jeopardize the generalizability of findings, perpetuate bias in data driven practices, and make new technologies dangerous for underrepresented groups. Key to progress towards inclusive and equitable gender practices is diagnosing the current status of bias and identifying where it comes from. In this mixed-methods study, we interviewed 13 HCI researchers to identify the potential bias factors, defined a systematic data collection procedure for meta-analysis of participant gender data, and created a participant gender dataset from 1,147 CHI papers. Our analysis provided empirical evidence for the underrepresentation of women, the invisibility of non-binary participants, deteriorating representation of women in MTurk studies, and characteristics of research topics prone to bias. Based on these findings, we make concrete suggestions for promoting inclusive community culture and equitable research practices in HCI.

Humans rely on categories to mentally organize and understand sets of complex objects. One such set, haptic devices, has myriad technical attributes that affect user experience in complex ways. Seeking an effective navigation structure for a large online collection, we elicited expert mental categories for grounded force-feedback haptic devices: 18 experts (9 device creators, 9 interaction designers) reviewed, grouped, and described 75 devices according to their similarity in a custom card-sorting study. From the resulting quantitative and qualitative data, we identify prominent patterns of tagging versus binning, and we report 6 uber-attributes that the experts used to group the devices, favoring affordances over device specifications. Finally, we derive 7 device categories and 9 subcategories that reflect the imperfect yet semantic nature of the expert mental models. We visualize these device categories and similarities in the online haptic collection, and we offer insights for studying expert understanding of other human-centered technology.

This conceptual essay uses the notion of texture to articulate the relationship between data infrastructure (the attributes and value parameters that give data its shape) and data environment (the mode of implementation in which data is stored and manipulated). We take experimental datasets that we authored with unorthodox, weird data infrastructure and translate those datasets from one data evironment to another. In performing these translations, we surface integration as a design activity. Integration work is often tedious, mundane, and technical--but it is nonetheless design. We show how texture arises from the integration of material components, demonstrating the effects of integration work upon user experience.

Contributions from the crowd are not just content-sustainable systems require ongoing behind-the-scenes infrastructural work. In this paper, I explore potential strategies for motivating volunteer contributions to large-scale collaborative projects when volunteer contributions are procedural in nature and largely invisible in the published project. I use a user-driven classification system for a large, established, and growing fanfiction collection as an example of a successful project of this type. I compare the challenges and possibilities to those established in the study of open source, wiki, and citizen science projects, which share with classification design a need for distributed human contributions to procedural tasks. Textual analysis of recruiting and training documents, informed by prolonged engagement in the community, reveals strategies that diverge from other HCI research on motivation, such as a focus on work rather than fun and insider rather than public recognition.

Software is increasingly crucial to scholarship, yet the visibility and usefulness of software in the scientific record are in question. Just as with data, the visibility of software in publications is related to incentives to share software in reusable ways, and so promote efficient science. In this article, we examine software in publications through content analysis of a random sample of 90 biology articles. We develop a coding scheme to identify software “mentions” and classify them according to their characteristics and ability to realize the functions of citations. Overall, we find diverse and problematic practices: Only between 31% and 43% of mentions involve formal citations; informal mentions are very common, even in high impact factor journals and across different kinds of software. Software is frequently inaccessible (15%–29% of packages in any form; between 90% and 98% of specific versions; only between 24%–40% provide source code). Cites to publications are particularly poor at providing version information, whereas informal mentions are particularly poor at providing crediting information. We provide recommendations to improve the practice of software citation, highlighting recent nascent efforts. Software plays an increasingly great role in scientific practice; it deserves a clear and useful place in scholarly communication.

This paper presents findings from a field study of records managers that provides context for understanding how people see objects on varying media as long-lasting objects (or not). Part of the mandate of the profession of records management is long-term preservation of digital and paper records. At the site of the fieldwork for this study, research participants' tasks primarily consisted of examining individual case files to determine if the files should be kept or destroyed under the relevant rules set by higher-level management according to legal requirements. Close observation of work practices showed that application of records management rules varied depending on the medium of the records, despite the policy that records on varying media are equal in importance. The results of the study suggest that the perceived accessibility and obsolescence of digital objects deserve more attention in the exploration of the place of digital objects in human lives over the long-term.

Online‐community management is commonly presented as the facilitation of conversation and contributions, especially converting readers to contributors. However, the goal of many discussion communities is to produce a high‐quality knowledge resource, whether to improve external task performance or to increase reputation and site traffic. What do moderation practices look like when the community is focused on the creation of a useable knowledge resource rather than facilitating an inclusive conversation? Under what conditions is this style of moderation likely to be successful? We present a case study from online gaming—Elitist Jerks—in which aggressive moderation is used to transform a conversational medium into a high‐quality knowledge resource, using the strategy of open censorship. We present a content analysis of moderator comments regarding censored messages. Our analysis revealed differences in types of contributor mistakes and the severity of moderator actions: infractions that interfered with both conversation and resource quality were punished harshly, whereas a set of infractions that supported conversation but undermined resource quality were more respectfully removed. We describe a set of conditions under which moderators should intervene in the conversion of conversation to knowledge resource rather than the conversion of lurkers to contributors.

To enable efficient searching and consistent interpretation of information, traditional metadata design practice emphasizes precisely delineated attributes. These sharp boundaries, however, reject data points that lie outside permissible values. For example, a Gender attribute with associated Male and Female values may appear perfectly clear and unambiguous, in line with traditional standards. Increasingly, however, people have begun to identify themselves as both, neither, other, or dynamic gender, rejecting cleanly separated Male/Female duality. In this project, student designers used critical design to explore how the descriptive infrastructure of a database might foreground, instead of restrict, the "residual"-a term that encapsulates the ambiguity and plurality masked by simple category structures like Male/Female. Our findings suggest that "writing" a database to exploit the residual is enmeshed with "reading" the content being structured. We identify three modes of reading that characterize these designs, and we describe how the residual emerges from each mode.

Structured databases achieve effective searching and sorting by enacting sharply delineated category boundaries around their contents. While this enables precise retrieval, it also distorts identities that exist between category lines. A choice between Single and Married, for example, blurs distinctions within the Single group: single, perhaps, merely because same-sex marriage is not legal in one's locality. Sociologists Susan Leigh Star and Geoffrey Bowker describe such residual states as inevitable byproducts of information systems. To minimize residuality, traditional practice for descriptive metadata seeks to demarcate clear and objective classes. In this study, we use critical design to question this position by creating information collections that foreground the residual, instead of diminishing it. We then interrogate our design experiments with solicited critical responses from invited experts and student designers. Inspired by the anthropologist Tim Ingold, we argue that our experiments illuminate a form of interacting with databases characterized by notions of wayfaring, or inhabiting a space, as opposed to notions of transport, or reaching a known destination. We suggest that the form of coherence that shapes a wayfaring database is enacted through its flow, or fluid integration between structure and content.