Leonelli Sabina
Exeter Centre for the Study of the Life Sciences (Egenis) & Department of Sociology, Philosophy and Anthropology, University of Exeter, Byrne House, St Germans Road, Exeter, EX4 4PJ UK.
Eur J Philos Sci. 2019;9(2):22. doi: 10.1007/s13194-018-0246-0. Epub 2019 Jan 15.
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.
我提出了一个框架，该框架通过考虑数据和模型在科学实践中的用途，来阐明和区分它们在实证研究中的认知作用。在论证了苏佩斯对数据模型的描述在这方面存在不足之后，我讨论了植物表型探索性研究中的一个数据处理案例，并以此来突出旨在使数据可用作证据的实践与旨在使用数据来表征特定现象的实践之间的差异。然后我认为，一组对象是作为数据还是模型发挥作用，并不取决于它们物理属性的内在差异、抽象程度或生成它们所涉及的人为干预程度，而是取决于它们在识别和表征研究目标方面的独特作用。因此，本文提出了一种数据模型的描述，它建立在苏佩斯对数据实践的关注之上，但无需设定数据和模型的固定层级，也无需将数据模型定义为高度排他性的统计结构。
