Patient-generated health data (PGHD) is crucial for healthcare providers' decision making,
as it complements clinical data by providing a more holistic view of patients' daily conditions …

Creating datasets for ML is an inherently human endeavor, as the data's heterogeneity
mandates human intervention. However, most data workflows being one-time and hardly …

This paper discusses the emergent field of biocuration, taking it as a case of academic data
work. Biocurators organise, manage, and enrich the now vast quantities of data that are …

The increasing datafication of social life has led to a growing body of research on data work
which focusses on new data practices like self-tracking, new professions like data analysts …

The Danish Immigration Service estimates that approximately 20% of decisions in asylum
cases are informed by data extracted from asylum seekers' mobile phones, enabling more …

We thought data to be simply given, but reality tells otherwise; it is costly, situation-
dependent, and muddled with dilemmas, constantly requiring human intervention. The ML …

Drawing from a longitudinal case study, we inspect the activities of an expanding team of
scientists and their collaborators as they sought to develop a novel software pipeline that …

Large language models (LLMs) stand to reshape traditional methods of working with data.
While LLMs unlock new and potentially useful ways of interfacing with data, their use in …

Natural Language Processing (NLP) techniques have been increasingly integrated into
clinical projects to advance clinical decision-making and improve patient outcomes. Such …

Within CSCW, there is a robust body of literature examining the infrastructures, institutions,
and labor processes enabling pervasive processes of datafication. Key public sectors and …