Data Matter(s): Legitimacy, Coding, and Qualifications-of-Life
Data Matter(s): Legitimacy, Coding, and Qualifications-of-Life
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数据问题：合法性、编码和生活资格
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发表时间：
2011
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通讯作者：
Matthew W. Wilson
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作者：
Matthew W. Wilson
数据是地理技术的核心，为地理调查提供了途径。因此，数据的重要性对于参与使用这些技术的人来说很重要。本文理解“物质”的物质意义上，即数据是从具体实践中产生的产品，并在情感意义上，数据是富有想象力的，生成的，和唤起。我在美国西雅图的一个社区调查项目的讨论中考察了这些存在感和意义感。在这个为期四年的项目中，十个社区的居民被要求使用手持电脑收集有关社区街道的数据。居民们通过定位受损的人行道和电话亭上的涂鸦等物体来追踪“资产”和“赤字”。然后，这些数据记录被上传到由当地非营利组织管理的中央服务器。该非营利组织与社区居民合作，帮助将这些关于他们不断变化的社区的数据与市政府机构联系起来。在这里，我认为，这些数据实践的合法性是通过标准化和客观化的过程，这些过程transduct城市空间。我问，由于参与性制图做法针对的是管理机构及其数据产品，这对所产生的知识种类及其合法性有何影响？换句话说，数据如何变得重要？
Data are central to geographical technologies and provide the pathways in which geographic investigations are forwarded. The mattering of data is therefore important to those engaging in participatory use of these technologies. This paper understands ‘mattering’ both in the material sense, that data are products resulting from specific practices, and in the affective sense, that data are imaginative, generative, and evocative. I examine these senses of mattering, of both presence and significance, in a discussion of a community survey project held in Seattle, USA. During this four-year project, residents in ten neighborhoods were asked to collect data about their community streets using handheld computers. Residents tracked ‘assets’ and ‘deficits’ by locating objects such as damaged sidewalks and graffiti on telephone booths. These data records were then uploaded to a central server administered by a local nonprofit organization. The nonprofit worked with community residents to help link these data about their changing neighborhoods to agencies in the municipal government. Here, I argue that the legitimacy of these data practices is constructed through processes of standardization and objectification and that these processes transduct urban space. I ask, as participatory mapping practices target governing agencies with their data products, what are the implications for the kinds of knowledge produced and for its legitimacy? In other words, how does data come to matter?