Authors
Sabina Leonelli
University of Exeter
Abstract
I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs.
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DOI 10.1007/s13194-018-0246-0
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References found in this work BETA

Saving the Phenomena.James Bogen & James Woodward - 1988 - Philosophical Review 97 (3):303-352.
Modelling and Representing: An Artefactual Approach to Model-Based Representation.Tarja Knuuttila - 2011 - Studies in History and Philosophy of Science Part A 42 (2):262-271.

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Citations of this work BETA

Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
The Role of Replication in Psychological Science.Samuel C. Fletcher - 2021 - European Journal for Philosophy of Science 11 (1):1-19.
The Evidence for the Accelerating Universe: Endorsement and Robust Consistency.Genco Guralp - 2020 - European Journal for Philosophy of Science 10 (2):1-52.

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