Data are versatile objects that can travel across contexts. While data's travels have been widely discussed, little attention has been paid to the sites from where and to which data flow. Drawing upon ethnographic fieldwork in two connected data-intensive laboratories and the concept of domestication, we explore what it takes to bring data 'home' into the laboratory. As data come and dwell in the home, they are made to follow rituals, and as a result, data are reshaped and form ties with the laboratory and its practitioners. We identify four main ways of domesticating data. First, through storytelling about the data's origins, data practitioners draw the boundaries of their laboratory. Second, through standardization, staff transform samples into digital data that can travel well while ruling what data can be let into the home. Third, through formatting, data practitioners become familiar with their data and at the same time imprint the data, thus making them belong to their home. Finally, through cultivation, staff turn data into a resource for knowledge production. Through the lens of domestication, we see the data economy as a collection of homes connected by flows, and it is because data are tamed and attached to homes that they become valuable knowledge tools. Such domestication practices also have broad implications for staff, who in the process of 'homing' data, come to belong to the laboratory. To conclude, we reflect on what these domestication processes-which silence unusual behaviours in the data-mean for the knowledge produced in data-intensive research.

中文翻译：

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驯化数据：数据经济中的旅行和价值创造。


数据是可以跨上下文传播的多功能对象。虽然数据的传输已被广泛讨论，但很少有人关注数据从何处流向何处。利用两个相互连接的数据密集型实验室的人种学田野调查和驯化概念，我们探索如何将数据“带回家”到实验室。当数据来到家中并驻留在家中时，它们必须遵循仪式，结果，数据被重塑并与实验室及其从业者建立联系。我们确定了数据归化的四种主要方法。首先，通过讲述数据起源的故事，数据从业者划定了实验室的界限。其次，通过标准化，工作人员将样本转化为可以顺利传输的数字数据，同时决定哪些数据可以进入家庭。第三，通过格式化，数据从业者熟悉自己的数据，同时给数据打上烙印，让数据成为自己的家。最后，通过培育，员工将数据转化为知识生产的资源。通过驯化的视角，我们将数据经济视为通过流连接的家庭的集合，正是因为数据被驯服并依附于家庭，它们才成为有价值的知识工具。这种驯化做法对工作人员也有广泛的影响，他们在“归巢”数据的过程中逐渐属于实验室。总之，我们反思这些驯化过程（使数据中的异常行为沉默）对于数据密集型研究中产生的知识意味着什么。