Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that allows that science to slip into (...) the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)

The essay analyses the importance and the limits of Evolutionary Epistemology . Firstly, the history of EE is shortly described - especially its history in the last century. Secondly, its main arguments are reproduced. Thirdly, the points are treated in which EE really signifies a progress in comparison with traditional epistemology. Fourthly, however, it is shown that it does not solve at all the central problem of epistemology - the validity claim of knowledge. Only a broader philosophical framework - that (...) of objective idealism - could reconcile the validity dimension with the genetic insights of EE. (shrink)

The essay analyses the importance and the limits of Evolutionary Epistemology (EE). Firstly, the history of EE is shortly described — especially its history in the last century. Secondly, its main arguments are reproduced. Thirdly, the points are treated in which EE really signifies a progress in comparison with traditional epistemology. Fourthly, however, it is shown that it does not solve at all the central problem of epistemology — the validity claim of knowledge. Only a broader philosophical framework — that (...) of objective idealism — could reconcile the validity dimension with the genetic insights of EE. (shrink)

The paper examines some of the significant new developments in the epistemological framing of systems theory, and their application within the information and management sciences. Specifically, the article argues that Information Systems – at its heart a systems-science – requires an ongoing discourse into how the metaphors of ‘living systems’, ‘complex systems’, and ‘complexity’ apply to the theoretical foundations of the IS discipline at large. Pragmatically, the implications of developing a complex and living systems framework to investigate IS phenomena has (...) the capacity to synthesise the very way information systems researchers consider their discipline, and the scientific inquiry of it. The “information system” becomes a decentralised, complex and evolving entity, where notions of chaos theory; system self-organisation; autopoietic and dissipative networks; emergence; entropy; and nonlinear dynamics; provide a rich and novel way to investigate system behaviours, human cognitive behaviours, and the management and business contexts in which those behaviours occur. (shrink)