Starting with some illustrative examples, I develop a systematic account of a specific type of experimentation--an experimentation which is not, as in the "standard view", driven by specific theories. It is typically practiced in periods in which no theory or--even more fundamentally--no conceptual framework is readily available. I call it exploratory experimentation and I explicate its systematic guidelines. From the historical examples I argue furthermore that exploratory experimentation may have an immense, but hitherto widely neglected, epistemic significance.

: The increasing attention on experiment in the last two decades has led to important insights into its material, cultural and social dimensions. However, the role of experiment as a tool for generating knowledge has been comparatively poorly studied. What questions are asked in experimental research? How are they treated and eventually resolved? And how do questions, epistemic situations, and experimental activity cohere and shape each other? In my paper, I treat these problems on the basis of detailed studies of (...) research practice. After presenting several cases from the history of electricity—Dufay, Ampère, and Faraday—I discuss a specific type of experiment—the "exploratory experiment"—and analyze how it works in concept formation. I argue that a fuller understanding of experiment can only be achieved by intertwining historical and philosophical perspectives in such a way that the very separation of the two become questioable. (shrink)

It is considered in some quarters that hypothesis‐driven methods are the only valuable, reliable or significant means of scientific advance. Data‐driven or ‘inductive’ advances in scientific knowledge are then seen as marginal, irrelevant, insecure or wrong‐headed, while the development of technology—which is not of itself ‘hypothesis‐led’ (beyond the recognition that such tools might be of value)—must be seen as equally irrelevant to the hypothetico‐deductive scientific agenda. We argue here that data‐ and technology‐driven programmes are not alternatives to hypothesis‐led studies in (...) scientific knowledge discovery but are complementary and iterative partners with them. Many fields are data‐rich but hypothesis‐poor. Here, computational methods of data analysis, which may be automated, provide the means of generating novel hypotheses, especially in the post‐genomic era. BioEssays 26:99–105, 2004. © 2003 Wiley Periodicals, Inc. (shrink)

Philosophers of experiment have acknowledged that experiments are often more than mere hypothesis-tests, once thought to be an experiment's exclusive calling. Drawing on examples from contemporary biology, I make an additional amendment to our understanding of experiment by examining the way that `wide' instrumentation can, for reasons of efficiency, lead scientists away from traditional hypothesis-directed methods of experimentation and towards exploratory methods.