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In this paper, we describe how critical data designers have created projects that 'push back' against the eclipse of environmental problems by dominant orders: the pioneering pollution database Scorecard, released by the US NGO Environmental Defense Fund in 1997; the US Environmental Protection Agency's EnviroAtlas that brings together numerous data sets and provides tools for valuing ecosystem services; and the Houston Clean Air Network's maps of real-time ozone levels in Houston. Drawing on ethnographic observations and interviews, we analyse how critical data designers turn scientific data and findings into claims and visualisations that are meaningful in contemporary political terms. The skills of critical data designers cross scales and domains; they must identify problems calling for public consideration, and then locate, access, link, and create visualisations of data relevant to the problem. We conclude by describing hazards ahead in work to leverage Big Data to understand and address environmental problems. Critical data designers need to understand what counts as a societal problem in a particular context, what doesn't, what is seen as connected and not, what is seen as ethically charged, and what is exonerated and discounted. Such recognition is produced through interpretive, 'close reading' of the historical moment in which they operate.

Recent research indicates that asthma is more complicated than already recognized, requiring a multilateral approach of study in order to better understand its many facets. Apart from being a health problem, asthma is seen as a knowledge problem, and as we argue here, a cultural problem. Employing cultural analysis we outline ways to challenge conventional ideas and practices about asthma by considering how culture shapes asthma experience, diagnosis, management, research, and politics. Finally, we discuss the value of viewing asthma through multiple lenses, and how such "explanatory pluralism" advances transdisciplinary approaches to asthma.

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Addressing the most pressing contemporary social, environmental, and technological challenges will require integrating insights and sharing data across disciplines, geographies, and cultures. Strengthening international data sharing networks will not only demand advancing technical, legal, and logistical infrastructure for publishing data in open, accessible formats; it will also require recognizing, respecting, and learning to work across diverse data cultures. This essay introduces a heuristic for pursuing richer characterizations of the "data cultures" at play in international, interdisciplinary data sharing. The heuristic prompts cultural analysts to query the contexts of data sharing for a particular discipline, institution, geography, or project at seven scales-the meta, macro, meso, micro, techno, data, and nano. The essay articulates examples of the diverse cultural forces acting upon and interacting with researchers in different communities at each scale. The heuristic we introduce in this essay aims to elicit from researchers the beliefs, values, practices, incentives, and restrictions that impact how they think about and approach data sharing-not in an effort to iron out differences between disciplines, but instead to showcase and affirm the diversity of traditions and modes of analysis that have shaped how data gets collected, organized, and interpreted in diverse settings.