Paper by Jason A. Martin, Lindita Camaj & Gerry Lanosga: “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….(More)”.
Scrape, Request, Collect, Repeat: How Data Journalists Around the World Transcend Obstacles to Public Data
How to contribute:
Did you come across – or create – a compelling project/report/book/app at the leading edge of innovation in governance?
Share it with us at info@thelivinglib.org so that we can add it to the Collection!
About the Curator
Get the latest news right in you inbox
Subscribe to curated findings and actionable knowledge from The Living Library, delivered to your inbox every Friday
Related articles
DATA
Data as medicine’s backbone: redefining its value to foster innovation in the data economy
Posted in September 17, 2025 by Stefaan Verhulst
artificial intelligence, DATA
We Tested AI Impact Assessments. Here’s What We Learned.
Posted in September 16, 2025 by Stefaan Verhulst
DATA
We have a lot of valuable health data. Why is it so hard to use?
Posted in September 16, 2025 by Stefaan Verhulst