This text reports on the impact of a training course offered by a multiplier trainer from the School of Data network.
On July the 5th I had the opportunity of conducting an real life workshop in collaboration with Data Crítica, Open Knowledge Foundation and the German magazine Lateinamerika Nachrichten, focusing on the fundamentals of data journalism, with 15 participants registered from Lateinamerika Nachrichten, Agencia Proceso and freelance journalists. The session was designed to equip participants with essential skills needed in today’s data-driven journalism landscape and incorporating a new tool by the Open Knowledge Foundation: the Open Data Editor (ODE) in the data pipeline for journalists in Berlin. All of the stages of the data pipeline were infused with the Data Crítica methodology, based on questioning, interviewing the database creation context, what dynamics lie behind them and how to know and communicate its limits.
In paralel, during 4 weeks of July I gave out the workshop “Introduction to Data Journalism” in collaboration with the Buenos Aires journalist Union (Sipreba) in Argentina, to a cohort of 45 journalists from outlets such as La Nación, El Diario AR, Agencia Télam, Salta 12, TV Pública, BigBang, El Destape, Radio Nacional, Diario Castellanos, Diario Digital, Diario Huarpe, Diario de Cuyo, Futurock and others, as well as some journalism students.
The methodology
Data Crítica’s methodology has been proven on journalism production and workshops over 7 years. It consists on introducing a critical framework to the data pipeline technical work, on each stage. It consists on:
- Questioning power behind datasets: origins, motivations, limits and possible biases.
- Understanding the different ways to gather information and structure it into tabular dataframes.
- Request for or build data into the most granular way possible, incorporating differences in contexts that bring up power dynamics, such as gender, race or economic position
- Understanding the basic operations of data analysis: counting and comparing, and how to use tools to facilitate these tasks.
- Making sure counting and comparing makes sense: by cleaning and arranging the data properly. At these stage, the introduction of the Open Data Editor to asess right away the overall quality of the data gathered from open sources, and introducing ODE’s framework for looking for completion, precision and consistency.
- Interrogate the databases posing investigation hypothesis and questions to the data via analysis and exploratory visualization.
- Contrast findings to hypothesis.
- Communicate specific findings in an editorial though precise way.
Key Takeaways
Throughout the workshop, I emphasized that data analysis in the context of journalism is but one more tool of a reporter toolkit, and that the same scrutiny that we pose to other sources must be posed to a data source. Data preparation through Open Data Editor and other tools is paramount to finding solid insights in data. Beyond technical capacities, the workshop emphasized that imagination to gather data and visualize it is more relevant than technical abilities, which compiled tools for extracting, cleansing and visualizing facilitate in the end. By the end of the IRL workshop, a representative of each of four teams formed during the session downloaded, cleaned, analyzed and visualized data on paper, before finally jumping to digital data visualization.
Looking Forward
The enthusiasm and engagement from participants demonstrated the growing interest in data-driven journalism. As we continue to live in an increasingly data-rich world, these skills become ever more crucial for modern journalists.
The workshop served as a stepping stone for participants to explore the vast possibilities that data journalism offers for amplifying their work, equipping them with the tools and knowledge to tell more impactful stories through data.
About the Open Data Editor
The Open Data Editor (ODE) is Open Knowledge’s new open source desktop application for nonprofits, data journalists, activists, and public servants, aiming at helping them detect errors in their datasets. It’s a free, open-source tool designed for people working with tabular data (Excel, Google Sheets, CSV) who don’t know how to code or don’t have the programming skills to automatise the data exploration process.
Simple, lightweight, privacy-friendly, and built for real-world challenges like offline work and low-resource settings, ODE is part of Open Knowledge’s initiative The Tech We Want — our ambitious effort to reimagine how technology is built and used.
And there’s more! ODE comes with a free online course that can help you improve the quality of your datasets, therefore making your life/work easier.
↪ Take the course: Learn how to use ODE
All of Open Knowledge’s work with the Open Data Editor is made possible thanks to a charitable grant from the Patrick J. McGovern Foundation. Learn more about its funding programmes here.
