As a nascent field within the academy, the contours, attributes, and bounties of data science are still indeterminate and contested. We studied how participants in an initiative to establish data science at a large American research university defined data science and articulated their relationships to the field. We discuss two contrasting visions for data science among our research participants. One vision is a transdisciplinary view portraying data science as a phenomenon with transcendent, appropriative, and impositional qualities that sits apart from academic domains. Another view of data science-one that was far more prevalent among our research subjects-casts data science as grounded, relational, and adaptive, emerging from crosspollination of numerous academic domains. We argue that this latter formulation represents a more quotidian reality of data science and positions the field as an extradiscipline, defined as a field that exists to facilitate the exchange of knowledge, skills, tools, and methods from an indeterminate and fluctuating set of disciplinary perspectives while conserving the boundaries of those disciplines. We argue that the dueling transdisciplinary and extradisciplinary visions for data science have important implications for how the field will mature, and that the extradiscipline concept opens novel directions for studying academic knowledge production in STS, contributing additional precision to the literature on disciplinarity and its permutations.

中文翻译：

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学术数据科学：跨学科和超学科的愿景。


作为学术界的一个新兴领域，数据科学的轮廓、属性和价值仍然不确定且存在争议。我们研究了美国一所大型研究型大学建立数据科学倡议的参与者如何定义数据科学并阐明他们与该领域的关系。我们在研究参与者中讨论了两种截然不同的数据科学愿景。一种愿景是一种跨学科的观点，将数据科学描绘成一种超越学术领域、具有超越性、专有性和强制性品质的现象。数据科学的另一种观点（在我们的研究主题中更为普遍）认为数据科学是扎根的、关系性的和适应性的，是从众多学术领域的交叉授粉中产生的。我们认为，后一种表述代表了数据科学更日常的现实，并将该领域定位为一门外学科，定义为一个旨在促进从一组不确定且波动的学科角度交流知识、技能、工具和方法的领域同时保留这些学科的界限。我们认为，数据科学的跨学科和超学科愿景对这个领域的成熟具有重要意义，并且超学科概念为研究 STS 中的学术知识生产开辟了新的方向，为有关学科性及其排列的文献提供了额外的精确性。