This article outlines a philosophy of science in practice that focuses on the engineering sciences. A methodological issue is that these practices seem to be divided by two different styles of scientific reasoning, namely, causal-mechanistic and mathematical reasoning. These styles are philosophically characterized by what Kuhn called ?disciplinary matrices?. Due to distinct metaphysical background pictures and/or distinct ideas of what counts as intelligible, they entail distinct ideas of the character of phenomena and what counts as a scientific explanation. It is (...) argued that the two styles cannot be reduced to each other. At the same time, although they are incompatible, they must not be regarded as competing. Instead, they produce different kinds of epistemic results, which serve different kinds of epistemic functions. Moreover, some scientific breakthroughs essentially result from relating them. This view of complementary styles of scientific reasoning is supported by pluralism about metaphysical background pictures. (shrink)

Recently, information retrieval is shown to be a science by mapping information retrieval scientific study to scientific study abstracted from physics. The exercise was rather tedious and lengthy. Instead of dealing with the nitty gritty, this paper looks at the insights into how computer science can be made into a science by using that methodology. That is by mapping computer science scientific study to the scientific study abstracted from physics. To show the mapping between computer science and physics, we need (...) to define what is engineering science which computer science belongs to. Some principles and assumptions of engineering science theory are presented. To show computer science is a science, we presented two approaches. Approach 1 considers computer science as simulation of human behaviour similar to the goal of artificial intelligence. Approach 2 is closely related to the actual activities in computer science, and this approach considers computer science based on the theory of computation. Finally, we answer some of the common outstanding issues about computer science to convince our reader that computer science is a science. (shrink)

In silicio design plays a fundamental role in the endeavour to synthesise biological systems. In particular, computer-aided design software enables users to manage the complexity of biological entities that is connected to their construction and reconfiguration. The software’s graphical user interface bridges the gap between the machine-readable data on the algorithmic subface of the computer and its human-amenable surface represented by standardised diagrammatic elements. Notations like the Systems Biology Graphical Notation , together with interactive operations such as drag & drop, (...) allow the user to visually design and simulate synthetic systems as ‘bio-algorithmic signs’. Finally, the digital programming process should be extended to the wet lab to manufacture the designed synthetic biological systems. By exploring the different ‘faces’ of synthetic biology, I argue that in particular computer-aided design is pushing the idea to automatically produce de novo objects. Multifaceted software processes serve mutually aesthetic, epistemic and performative purposes by simultaneously black-boxing and bridging different data sources, experimental operations and community-wide standards. So far, synthetic biology is mainly a product of digital media technologies that structurally mimic the epistemological challenge to take both qualitative as well as quantitative aspects of biological systems into account in order to understand and produce new and functional entities. (shrink)

Unlike basic sciences, scientific research in advanced technologies aims to explain, predict, and (mathematically) describe not phenomena in nature, but phenomena in technological artefacts, thereby producing knowledge that is utilized in technological design. This article first explains why the covering-law view of applying science is inadequate for characterizing this research practice. Instead, the covering-law approach and causal explanation are integrated in this practice. Ludwig Prandtl's approach to concrete fluid flows is used as an example of scientific research in the engineering (...) sciences. A methodology of distinguishing between regions in space and/or phases in time that show distinct physical behaviours is specific to this research practice. Accordingly, two types of models specific to the engineering sciences are introduced. The diagrammatic model represents the causal explanation of physical behaviour in distinct spatial regions or time phases; the nomo-mathematical model represents the phenomenon in terms of a set of mathematically formulated laws. (shrink)