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Rawification and the careful generation of open government data

机译:原始化和精心生成公开的政府数据

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Drawing on a two-year ethnographic study within several French administrations involved in open data programs, this article aims to investigate the conditions of the release of government data - the rawness of which open data policies require. This article describes two sets of phenomena. First, far from being taken for granted, open data emerge in administrations through a progressive process that entails uncertain collective inquiries and extraction work. Second, the opening process draws on a series of transformations, as data are modified to satisfy an important criterion of open data policies: the need for both human and technical intelligibility. There are organizational consequences of these two points, which can notably lead to the visibilization or the invisibilization of data labour. Finally, the article invites us to reconsider the apparent contradiction between the process of data release and the existence of raw data. Echoing the vocabulary of one of the interviewees, the multiple operations can be seen as a rawification' process by which open government data are carefully generated. Such a notion notably helps to build a relational model of what counts as data and what counts as work.
机译:本文基于在涉及开放数据计划的几个法国政府中进行的为期两年的人种志研究,本文旨在研究政府数据发布的条件-开放数据政策要求的原始性。本文介绍了两种现象。首先,开放式数据不是理所当然的,而是通过一个渐进的过程在主管部门中出现的,该过程需要不确定的集体查询和提取工作。其次,随着数据的修改以符合开放数据政策的重要标准:对人员和技术清晰度的需求,开放过程需要进行一系列的转换。这两个方面都有组织上的后果,特别是可以导致数据劳动的可视化或不可视化。最后,本文邀请我们重新考虑数据发布过程与原始数据存在之间的明显矛盾。与被访者之一的词汇相呼应,多次操作可以看作是精简过程,通过该过程可以仔细生成公开的政府数据。这种概念尤其有助于建立什么算作数据以及什么算作工作的关系模型。

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