A conceptual mapping of big data is necessary which would most obviously draw upon basic mapping principles (metaphorically and literally) and epistemological models. For example, one dimension of a big data map is numeracy. In the conceptualization of big data, so far the context has been individuated information, information about individual units, like people (e.g.; personal data), and the tensions between the subject of the data and the user of the data, namely institutions. There is now an emergent category (e.g.; group data), the sense of data arising from and belonging to a group.
The quantified self is a vanguard paradigm for understanding personal data and urban data a similar vanguard paradigm for understanding group data. The quantified self is inherently a big data problem, as manually-tracked ‘small data’ is now being replaced by automatically-collected ‘big data,’ and cloud-based methods are required for data processing, analysis, and storage.
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