Domain experts play an essential role in data science by helping data scientists situate their technical work beyond the statistical analysis of large datasets. How domain experts themselves may engage with data science tools as a type of end-user remains largely invisible. Understanding data science as domain expert-driven depends on understanding how domain experts use data. Drawing on an ethnographic study of a craft brewery in Korea, we show how craft brewers worked with data by situating otherwise abstract data within their brewing practices and settings. We contribute theoretical insight into how domain experts use data distinctly from technical data scientists in terms of their view of data (situated vs. abstract), purposes for engaging with data (guiding processes over predicting outcomes), and overall goals of using data (flexible control vs. precision). We propose four ways in which working with data can be supported through the design of data science tools, and discuss how craftwork can be a useful lens for integrating domain expert-driven understandings of data science into CSCW and HCI research.

People with visual impairments (PVI) access photos through image descriptions. Thus far, research has studied what PVI expect in these descriptions mostly regarding functional purposes (e.g., identifying an object) and when engaging with online, publicly available images. Extending this research, we interviewed 30 PVI to understand their expectations for image descriptions when viewing, taking, searching, and reminiscing with personal photos on their own devices. We show how their expectations varied across photo activities and often went well beyond identifying objects in photos. Based on our fndings, we propose design opportunities for generating and providing image descriptions for personal photo use by PVI. The design opportunities for PVI also point to novel support for the sighted for using image descriptions to enrich their experience of photos. CCS CONCEPTS• Human-centered computing → Accessibility.

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Research on data science has largely viewed data as an abstract input in service of algorithms developed by data scientists. In this view, data science activities are made sustainable by the efficient flow of data to improve the algorithms. Recent studies in CSCW and HCI, however, point to how the effectiveness of algorithms critically depends on sustainably collecting reliable, complete data situated in domain experts’ practices and settings. Drawing on ethnographic fieldwork and a pilot machine learning project at a craft brewery, we describe three types of situations where brewers’ data practices led to unreliable, incomplete data, and how such data practices limited the effectiveness of data science activities. We analyze sources of misalignment between their data practices and data science activities, which we use to offer design implications for sustainability. Extending research on end-user software development that views sustainability as driven by domain experts as ‘owners of problems,’ our study proposes data science research driven by domain experts as ‘owners of data.’

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Coordinating organizational routines is a strategic challenge in contexts ranging from healthcare to software development. Yet, we have few theories of the design of routines. This paper compares field data on routines at two Korean restaurants to theorize their design. We identified a core coordination challenge as the need for concurrency-the simultaneous coordination of diverse activities of indeterminate order. The restaurants enabled concurrency using distinct solutions for providing information to agents about their routine activities. We normatively frame these solutions as firm-level strategies for coordinating routines based on uniformity (providing information about fixed sequences of activities) or compatibility (providing information about particular performances of activities). While prior work assumes strategies for coordinating routines depend on extensive codification, our framework shows how extensive codification is specific to a uniformity strategy. We argue that the compatibility strategy characterizes how firms increasingly coordinate routines amid blurring firm boundaries and discuss implications for landscape design.

This paper examines "repairedness" - the contingently stable, working version of an artifact under repair that is negotiated out of multiple possible versions to bring about the temporary conclusion of repair work. Our paper draws on an ethnographic study of an analog electronics repair community in Seoul, South Korea to develop two contributions. First, studying processes of negotiating the repairedness of an artifact accounts for contingency in the properties of the artifact itself, which differs from contingencies in collaborative work practices that have been a focus of CSCW research on repair. Second, a concept of repairedness highlights how ongoing processes of interacting with an artifact nonetheless need to be brought to contingent conclusions, suggesting that an artifact's properties are a valuable site for sustainable engagement. These contributions help CSCW research on repair account for the multiplicity of artifacts highlighted by STS scholars as integral to how humans sustainably engage with artifacts in their practices.