datajournalismi

Datajournalismi is the practice of using data as a central source to investigate and communicate news. It blends traditional reporting with quantitative analysis and data visualization to explain trends, test claims, and reveal patterns that might be hidden in prose alone.

The workflow typically includes locating data from public records, government databases, surveys, or scraping APIs; cleaning and normalizing data; linking datasets; and applying exploratory analysis and statistics to interpret results. Journalists often collaborate with data scientists to build reproducible analyses and to validate findings.

Presentations rely on charts, maps, dashboards, and interactive graphics that make complex information accessible, with datasets and code shared to support transparency. The goal is to supplement narrative with verifiable evidence while preserving journalistic context and storytelling.

Datajournalismi emerged in the early 2000s and has grown with open data movements and better tools. Notable outlets include The Guardian, The New York Times, ProPublica, and national or regional newsrooms that publish data-driven investigations on budgets, crime, health, education, elections, and the environment.

Ethical and practical considerations include confirming data provenance and quality, protecting privacy, avoiding misinterpretation or bias, and ensuring accountability. Reproducibility, clear sourcing, and accessibility for diverse audiences are central to responsible practice.