DIMENSIONS OF DATA QUALITY FOR VALUES IN SMART CITIES DATAFICATION PRACTICES

Abstract

Data quality facilitates data interoperability for optimal decision-making in smart cities datafication. But there are few studies on how technologists (e.g., data scientists), governance people (e.g., municipal workers), and third-party collaborators (e.g., smart city services vendors) assess data quality together in smart cities datafication. This paper offers a response to this knowledge gap, using interviews (n=10) with municipal workers, data scientists and smart city services vendors, and data structure documents (n=8) in a situated case, the Stavanger (Norway) smart city. Implicit the paper’s results is that data quality is a floating signifier – comprising the different articulations of data scientists, municipal workers and services vendors in assessment. This generates friction with implications on data interoperability. This paper therefore posits that assessing data quality in smart cities datafication is ambiguous, but not empty. It fluctuates between the articulations of data scientists, municipal workers, and services vendors, with implications on data interoperability through the friction this generates. Keywords: data quality, data interoperability, floating signifier, frictions, smart city datafication