During my many years of research as historian and anthropologist of the sciences, in numerous interviews and less formal conversations with scientists of all kinds,  the most frequent expression I’ve heard used by someone referring to an admired colleague goes something like this: “She’s a great scientist – very careful…”  My current book project tries to elaborate, through scientists’ own words, what it means to be a “careful scientist,” and why what I call the “care of the data” is so essential to doing good science today.
We’ve known for a while that the practice of doing science – including both the experimental practices of the laboratory, and the theoretical practices of creating, developing, and recombining concepts – requires more than formal expertise, impeccable reasoning, strict logic, and exact, algorithmic methodologies, necessary as all those qualities are.  “Tacit knowledge,” “craft,” “a feeling for the organism,” or an ability to “muddle through” are but a few of the ways that scientists and analysts of science have named those ways of thinking and doing that are also essential to good, creative scientific work –  necessary supplements to the “scientific method” that are often difficult to formalize or articulate, and often escape attention, memory, and credit.  By introducing what, appropriating Michel Foucault, I call the “care of the data,” I am not staking any claim to originality, but rather re-opening and re-articulating a set of questions and concerns  recognized  as essential for a full understanding and appreciation of the sciences and scientists.
Today, genomicists (the scientists on whom I am currently most focused) spend much of their time caring for their data: figuring out how to handle the “avalanches” and “floods” of data now available to them, developing new interpretive techniques and tools that leverage the new data flows, collectively deliberating and debating about experimental standardization and validation, worrying over the ways complex findings will be taken up by the media and policy makers..  It is through the care of the data that many genomicists work out and realize what they consider to be good science, and “the good scientist:”  open to the data avalanche, welcoming its surprises and eagerly experimenting with them, but simultaneously cultivating a respect for the data flood’s openness to multiple interpretations, a keen awareness of its uncertainties, fragilities, and insufficiencies, a heightened sensitivity to its confounding excesses and its limitations.  Ways of caring for data are analogous to the ways of caring for the self  described by Foucault — historically specific, culturally imbricated, institutionally inscribed, and continually re-interrogated.  Understanding how scientists care for the data is a way to understand how society, culture and political-economy inhabit scientific practice, and shape scientists’ own conceptions of themselves as agents of ethics, and of historical change.
It’s this creative and disciplined scientific subject, the “careful scientist” — able to live and think well in a field of excess data, excess interpretation, and excess possibility, and thus able to think well about the question of complex entities and contested categories like “asthma” or “race” – that my book tries to illuminate.