Translating data into narratives

Abstract

Today more than ever, it is evident the role that data can play when designing policies. Not only can understandable data orient better strategies, but they can also enable reflexive practices within Public Administrations, giving directions for knowledge management and smarter governance. However, multiple gaps concur to affect data understanding and interpretation, hindering their subsequent translation into policy-valuable information. To tackle challenges related to data interpretation and usage, the article (i) illustrates a narrative approach for building profiles of cities as narrative feedback from sets of data and (ii) investigates their potential as a (self-)evaluation and a decision-making support device. The feedback structure relies on the conceptual model built for the DIGISER Project, which investigated multidimensional digital transition processes across European cities. Dynamic feedback retrieves data from the project dataset, translating them into discursive form. The effectiveness of the approach and its device is validated through a qualitative enquiry on a textual excerpt provided to three different departments of one of the cities that participated in the survey. The study corroborates that designing narrative feedback as semantic interpretations can trigger understanding, (self-)reflection and support policy change, informing policy formulation and facilitating cross-silo interactions across administrative units engaged in digital transformation processes.