Twelve Challenges for Critical Data Practice

As we’re in the final stages of editorial for the Data Journalism Handbook (forthcoming on Amsterdam University Press) Liliana Bounegru and I are curious to hear from those who have read and/or used the online beta of the book.

In particular we’re curious to learn about any projects or activities which were prompted by the “Twelve Challenges for Critical Data Practice” (copied below) as we finalise the book’s introduction. If you’re used or incorporated these into any data journalism projects or research, we’d love to hear from you. 📖 📝 ✨

Twelve Challenges for Critical Data Practice

Drawing on the time that we have spent exploring data journalism practices through the development of this book, we would like to conclude this introduction to the book with twelve challenges for “critical data practice.” These consider data journalism in terms of its capacities to shape relations between different actors as well as to produce representations about the world. Having been tested in the context of our research and teaching collaborations at King’s College London, they are intended as a prompt for aspiring data journalists, student group projects and investigations, researcher-journalist collaborations and other activities which aspire to organise collective inquiry with data without taking for granted the infrastructures, environments and practices through which it is produced.

1. How can data journalism projects tell stories both with and about data including the various actors, processes, institutions, infrastructures and forms of knowledge through which data is made?

2. How can data journalism projects tell stories about big issues at scale (e.g., climate change, inequality, multinational taxation, migration) while also affirming the provisionality and acknowledging the models, assumptions and uncertainty involved in the production of numbers?

3. How can data journalism projects account for the collective character of digital data, platforms, algorithms and online devices, including the interplay between digital technologies and digital cultures?

4. How can data journalism projects cultivate their own ways of making things intelligible, meaningful and relatable through data, without simply uncritically advancing the ways of knowing “baked into” data from dominant institutions, infrastructures and practices?

5. How can data journalism projects acknowledge and experiment with the visual cultures and aesthetics that they draw on, including through combinations of data visualisations and other visual materials?

6. How can data journalism projects make space for public participation and intervention in interrogating established data sources and re-imagining which issues are accounted for through data, and how?

7. How might data journalists cultivate and consciously affirm their own styles of working with data, which may draw on, yet remain distinct from areas such as statistics, data science and social media analytics?

8. How can the field of data journalism develop memory practices to archive and preserve their work, as well as situating it in relation to practices and cultures that they draw on?

9. How can data journalism projects collaborate around transnational issues in ways which avoid the logic of the platform and the colony, and affirm innovations at the periphery?

10. How can data journalism support marginalised communities to use data to tell their own stories on their own terms, rather than telling their stories for them?

11. How can data journalism projects develop their own alternative and inventive ways of accounting for their value and impact in the world, beyond social media metrics and impact methodologies established in other fields?

12. How might data journalism develop a style of objectivity which affirms, rather than minimises, its own role in intervening in the world and in shaping relations between different actors in collective life?

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