Data Repair

TL;DR

This ethnographic study explores data repair practices in Bangladesh, highlighting technical, linguistic, and ethical challenges faced by local repairers and their implications for data equity and HCI.

Contribution

It provides an in-depth ethnographic analysis of data repair work in a low-resource setting, emphasizing socio-technical and ethical dimensions often overlooked.

Findings

Data repair is constrained by limited access to high-precision tools and resources.

Repairers face linguistic barriers and ethical tensions in using external resources.

Pricing strategies reflect both technical effort and emotional labor involved in data repair.

Abstract

This paper investigates data repair practices through a six-month-long ethnographic study in Bangladesh. Our interviews and field observations with data repairers and related stakeholders found that, alongside the scarcity of high-precision machinery and access to advanced software, data repair work is constrained by cross-language learning resources and the protective nature of documenting, curating, and sharing the experiences and knowledge among local peers. Repairers turning to external resources such as foreign forums and LLMs also revealed their frustrating experiences and the postcolonial ethical tensions they encountered. We noted that both anticipated technical labor and the emotionality of data were taken into account for pricing the data repair job, which contributed to their market sustainability strategies. Engaging with repair, infrastructure, and data poverty discourse, we argue that data repair practices represent a crucial challenge and opportunity for HCI in advancing global efforts toward data equity.