Scrape, Request, Collect, Repeat: How Data Journalists Around the World Transcend Obstacles to Public Data

Abstract

ABSTRACT This study applies a typology of public data transparency infrastructure and the contextualism framework for analysing journalism practice to examine patterns in data journalism production. The goal was to identify differences in approaches to acquiring and reporting on data around the world based on comparisons of public data transparency infrastructure. Data journalists from 34 countries were interviewed to understand challenges in data access, strategies used to overcome obstacles, innovation in collaboration, and attitudes about open-data advocacy. Analysis reveals themes of different approaches to journalistic interventionism by overcoming structural obstacles and inventive techniques journalists use to acquire and build their own data sets even in the most restrictive government contexts. Data journalists are increasingly connected with colleagues, third parties, and the public in using data, eschewing notions of competition for collaboration, and using crowdsourcing to address gaps in data. Patterns of direct and indirect activism are highlighted. Results contribute to a better understanding of global data journalism practice by revealing the influence of public data transparency infrastructure as a major factor that constrains or creates opportunities for data journalism practice as a subfield. Findings also broaden the cross-national base of empirical evidence on the developing practices and attitudes of data journalists.