Working principles of data journalism

2024

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.32523/2616-7174-2024-149-4-7-18
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This article examines the development of data journalism in Kazakhstan and its practical applications. Data journalism enhances information processing by collecting, analyzing, and visualizing data. Modern tools like Python, Excel, and Tableau simplify journalists’ tasks and improve the accuracy of the presented information. Although data availability is growing in Kazakhstan, data journalism faces challenges due to limited sources or inconvenient formats. Internationally, open data portals significantly improve access to information. In Kazakhstan, the number of open data sources is increasing, providing journalists with better access to information, but the field remains in a developmental stage. Data journalism effectively conveys information not only through text but also visually, using infographics and charts for easier comprehension. The study highlights that data journalism in Kazakhstan is an emerging discipline shaped by globalization and new technologies. Its importance in the information age and its potential for further growth are becoming increasingly evident.