  In this paper I explore the scaffolding of normative assumptions that
supports Sabina Leonelli's implicit appeal to the values of epistemic integrity
and the global public good that conjointly animate the ethos of responsible and
sustainable data work in the context of COVID-19. Drawing primarily on the
writings of sociologist Robert K. Merton, the thinkers of the Vienna Circle,
and Charles Sanders Peirce, I make some of these assumptions explicit by
telling a longer story about the evolution of social thinking about the
normative structure of science from Merton's articulation of his well-known
norms (those of universalism, communism, organized skepticism, and
disinterestedness) to the present. I show that while Merton's norms and his
intertwinement of these with the underlying mechanisms of democratic order
provide us with an especially good starting point to explore and clarify the
commitments and values of science, Leonelli's broader, more context-responsive,
and more holistic vision of the epistemic integrity of data scientific
understanding, and her discernment of the global and biospheric scope of its
moral-practical reach, move beyond Merton's schema in ways that effectively
draw upon important critiques. Stepping past Merton, I argue that a combination
of situated universalism, methodological pluralism, strong objectivity, and
unbounded communalism must guide the responsible and sustainable data work of
the future.
