ABSTRACT
Data frictions concern all forms of data, including those relating to cities and urban life, and manifest in various ways. Coining the phrase 'data friction', historian Paul Edwards describes the struggles that ensue when attempting to move data and metadata from one format, organization, scale or context to another. Considering the long way from taking pictures of clouds to measuring urban economies, OLS data appears to be a non-sticky data source. The provisional categorization of sticky and non-sticky data seems increasingly untenable. The stickiness of social media data resists the operationalization in automatic pipelines for knowledge extraction and manifests itself in false positives that can only be identified and resolved by a close reading of the source. Ignoring stickiness of context can lead to cases where a terrorism suspect identified by unsupervised text analysis turns out to be the journalist who reported on the issue.
