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Scientific Modeling Versus Engineering Modeling: Similarities and Dissimilarities

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Abstract

This article aims to answer what I call the “constitution question of engineering modeling”: in virtue of what does an engineering model model its target system? To do so, I will offer a category-theoretic, structuralist account of design, using the olog framework. Drawing on this account, I will conclude that engineering and scientific models are not only cognitively but also representationally indistinguishable. I will finally propose an axiological criterion for distinguishing scientific from engineering modeling.

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Notes

  1. The philosophical literature on scientific representation is so vast and growing that I can mention only the surveys. Frigg and Nguyen (2017) have examined almost all views. Chakravartty (2010) has categorized them into the two groups of informational and functional theories. Boesch (2019) has recently developed a unifying picture of functional or agent-based accounts. For a brief sketch, see Frigg and Nguyen (2018).

  2. Among them are the use plan analysis of Houkes and Vermaas (2010), the explanationist account of van Eck (2016) and Galle’s (1999) action-based account in which the conception of design representation has a key role. Besides philosophical accounts, design theorists also have suggested several design theories, e.g. the concept-knowledge (C-K) theory of Hatchuel and Weil (2009), the Functional-Behavior-Structure account of Gero and Kannengiesser (2004) and the Functional Basis method of Stone and Wood (2000).

  3. Many thinkers attack such a distinction. For more on this, see footnote 20.

  4. For instance, Ubbink argues that “[t]he essential thing is that a model represents an object or matters of fact in virtue of its structure; so an object is a model ... of matters of fact if, and only if, their structures are isomorphic” (Ubbink 1960, 302), or French holds that “[e]ach of these claims [i.e. isomorphsim is not necessary for representation, isomorphism is not sufficient for representation and models denote and do not resemble] will be questioned and I will conclude by suggesting that, through appropriate modifications, a form of isomorphism [i.e. partial isomorphism] can serve to underpin representation in both the arts and science” (French 2003, 1473).

  5. The theories deploying non-symmetric morphisms such as homomorphism would meet the first objection (Bartels 2006). For more details about structuralism on representation, see Frigg and Nguyen (2017).

  6. Suárez’s account is deflationary in the sense that it aims not to answer the constitution question, but just to provide necessary conditions.

  7. To avoid Newman’s objection, the set A is not unconstrained (Bueno 2017). Otherwise, we can always ascribe a structure, being morphic to the model, to the target. As such, the intentional acts merely would carry out the representational burden.

  8. For a detailed defense of a hybrid account, see Bueno and French (2011).

  9. Galle calls the communication of the designer with herself “self-communication” (Galle 1999, 63).

  10. For more details, see Awodey (2010).

  11. Since being aspect is a functional relation, we cannot simply denote the aspect by “has” (Spivak and Kent 2012, 4).

  12. The mathematical notions to be introduced hereafter are not present in the olog framework.

  13. The olog language has been used in materials design studies. For example, see Giesa et al. (2012), Wong et al. (2012), and Cranford and Buehler (2012).

  14. Of course, there are some minor differences between the two kinds of modeling as reconstructed above. For instance, while the structures involved in scientific modeling are set-theoretic, the structures employed in engineering modeling are category-theoretic. These slight differences, however, are not substantial enough to fundamentally differentiate the two kinds of modeling. For in both cases the source and target of modeling are structures, the relation between them is structural, and intentional aspects matter for such relation. More importantly, The Elementary Theory of the Category of Sets (ECST) provides us with a machinery to derive set-theoretic notions from category-theoretic ones (Lawvere 1964).

  15. Emphases added in the above quotation illustrate this point.

  16. The constructive nature of target systems in high energy physics has already been discussed in the science studies literature (Galison et al. 1997; Pickering 1999).

  17. For a very brief history, see Weinberg (2004).

  18. Modern books on quantum field theory usually discuss the standard model (Schwartz 2014; Peskin 2018). For a more introductory book, see Goldberg (2017). The detection of the Higgs at the LHC has been narrated by Gagnon (2016).

  19. This does not mean that pure and applied scientists produce just, respectively, science and design representation. These given productions are merely final ones.

  20. Here it is taken for granted that there is a (though not clear-cut) distinction between science and engineering modeling. But there are many science and technology studies practitioners who deny any distinction between science and engineering (or between basic and applied science), advancing hybrid concepts such as technoscience (for more on this, see Channell 2017). For them, contextual (e.g. social, historical and political) factors have a key role in determining the meaning of the terms associated with these concepts (Latour 1987; Nordmann et al. 2011; Pielke 2012). There have recently been some attempts to reconcile these two approaches (e.g. Kant and Kerr 2019). The question whether the account proposed here would also do such a thing is interesting, but is beyond the scope of this article.

  21. I thank two anonymous referees for pointing out this worry to me.

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Acknowledgements

The paper has benefited greatly from valuable suggestions of two anonymous referees and the editors of this journal; I sincerely thank them. Thanks to Karim Thébault for reading a draft of this paper and providing useful comments. This article is a part of a project that has received funding from the Iran National Science Foundation (INSF) Grant number 95835408.

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    Aboutorab Yaghmaie

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Yaghmaie, A. Scientific Modeling Versus Engineering Modeling: Similarities and Dissimilarities. J Gen Philos Sci 52, 455–474 (2021). https://doi.org/10.1007/s10838-020-09541-3

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