Models in Search of Targets: Exploratory Modelling and the Case of Turing Patterns

  • Axel Gelfert
Part of the European Studies in Philosophy of Science book series (ESPS, volume 9)


Traditional frameworks for evaluating scientific models have tended to downplay their exploratory function; instead they emphasize how models are inherently intended for specific phenomena and are to be judged by their ability to predict, reproduce, or explain empirical observations. By contrast, this paper argues that exploration should stand alongside explanation, prediction, and representation as a core function of scientific models. Thus, models often serve as starting points for future inquiry, as proofs of principle, as sources of potential explanations, and as a tool for reassessing the suitability of the target system (and sometimes of whole research agendas). This is illustrated by a case study of the varied career of reaction-diffusion models in the study of biological pattern formation, which was initiated by Alan Turing in a classic 1952 paper. Initially regarded as mathematically elegant, but biologically irrelevant, demonstrations of how, in principle, spontaneous pattern formation could occur in an organism, such Turing models have only recently rebounded, thanks to advances in experimental techniques and computational methods. The long-delayed vindication of Turing’s initial model, it is argued, is best explained by recognizing it as an exploratory tool (rather than as a purported representation of an actual target system).


Exploratory models Scientific modelling Models Turing patterns Reaction-diffusion systems 



I would like to thank the conference participants at the GWP. 2016 meeting in Düsseldorf in March 2016 and at the workshop “Models in Science”, held at Lingnan University (Hong Kong) in March 2017, for their discussion and feedback. An anonymous referee provided especially helpful and incisive comments, for which I am grateful. Professor Shigeru Kondo at Osaka University kindly gave permission to reproduce the two images labelled as Figs. 14.3 and 14.4 above.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Philosophy, Literature, History of Science and TechnologyTechnical University of BerlinBerlinGermany

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