Data practices during COVID: Everyday sensemaking in a high-stakes information ecology.

. What this paper adds Everyday data practices can be variable and adaptable, and include engaging with data at different levels: scanning, looking closer, and puzzling through. Each of these modes involves different data practices.People, independently of their quantitative interpretation skills and disciplinary backgrounds, may engage differently with data (eg, avoiding versus delving deeper) based on their emotional responses, level of trust or interpersonal relationships that are evoked by the data.These everyday data practices have implications for people's sense of their own agency with data and involve emotional and trust-based relationships that shape their interpretations of data. These relational aspects of data literacy suggest productive directions for data literacy education. Implications for practice and/or policy Data literacy can be taught as a process that is inherently relational, for example, by discussing the ways in which learners are personally connected to different data, what emotions these connections evoke, and how that affects the ways in which they attend to, trust and interpret the data.Data literacy education can cultivate a wider range of data practices at a variety of depths of interaction, rather than prioritizing only in-depth inquiry.It may be helpful to include complex experiences with data sources that require learners to go beyond a binary "trustworthy/untrustworthy" distinction, so that learners can become more strategic, nuanced and intentional in forming a variety of trust relationships with different sources.Discussing how learners' everyday data practices interact with different data representations and tools can help them become more critically aware of the possible purposes, values, and risks associated with their everyday data practices.