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Despite the current attention toward the concept of data culture, a commonly accepted scope and definition is currently lacking. Addressing this conceptual fuzziness would be beneficial to pursue the development of knowledge on data culture in the public sector. The research aims at advancing theory by building a novel conceptualization of the constituent elements of data culture in local governments and their relationships.

For this purpose, the authors used a multi-method research design. More precisely, the authors conducted 12 semi-structured interviews with mayors and heads of administration from local governments, and a document analysis. The authors inductively mapped the findings to an existing heuristic featuring seven levels of data culture and extracted relationships between these levels.

The authors find several elements belonging to the data culture of local governments for each level of the existing generic heuristic and identify 24 influence relationships between these levels. The authors integrate these findings into the data culture model, which conceptualizes data culture in local governments.

The data culture model provides a strong theoretical basis for researchers to position their research and further advances knowledge on this still elusive concept. Practitioners can use the data culture model as a reflective tool to understand which elements impacted their current data behavior.

To the best of the authors’ knowledge, this is the first work to provide a conceptualization of data culture in local governments at this level of depth, and to conceptualize relationships between constituent elements of data culture.