People are increasingly subject to the tracking of data about them at their workplaces. Sensor tracking is used by organizations to generate data on the movement and interaction of their employees to monitor and manage workers, and yet this data also poses significant risks to individual employees who may face harms from such data, and from data errors, to their job security or pay as a result of such analyses. Working with a large hospital, we developed a set of intervention strategies to enable what we call "collective sensemaking" describing worker contestation of sensor tracking data. We did this by participating in the sensor data science team, analyzing data on badges that employees wore over a two-week period, and then bringing the results back to the employees through a series of participatory workshops. We found three key aspects of collective sensemaking important for understanding data from the perspectives of stakeholders: 1) data shadows for tempering possibilities for design with the realities of data tracking; 2) data transducers for converting our assumptions about sensor tracking, and 3) data power for eliciting worker inclusivity and participation. We argue that researchers face what Dourish (2019) called the "legitimacy trap" when designing with large datasets and that research about work should commit to complementing data-driven studies with in-depth insights to make them useful for all stakeholders as a corrective to the underlying power imbalance that tracked workers face.

Introducing data tracking of patients, doctors, medicine, or medical equipment holds promise to optimize workflows within hospitals. However, placing tracking devices and collecting data does not automatically translate into new workflows; instead, it requires careful considerations, knowledge about the activities tracked, and technical knowledge. In this paper, we study the interdisciplinary work involved when data tracking techniques are used to construe workflows within a real life work setting: architectural design of hospitals. We provide an ethnographic account from a unique study where two types of data tracking techniques were utilized in an existing hospital with the aim of informing the architectural design of a future hospital. The paper makes three contributions. First, we characterize the work involved in construing workflows based upon data tracking. Second, we discuss surveillance as an empirical category, which emerged in our study. Finally, we argue that to be able to construe workflows based upon data tracking, balancing the seamless boundary of privacy in work and surveillance in cooperation with the practitioners is of critical importance. Without support from the practitioners, data quality is at risk, and the resulting workflows might turn out 'flawed'.