Research: “Investigative open data journalism in Russia: actors, barriers and challenges”

This is a research paper that was accepted but not presented at the Global Investigative Journalism Conference 2017 Academic Track, which IJEC organized and covered.

Anastasia Valeeva from the Reuters Institute for the Study of Journalism at Oxford researched the culture of data reporting in Russian investigative outlets through interviews, case studies and qualitative content analysis.

“In this study, I wanted to show how open data is used for investigative storytelling in Russia, and what are the barriers that prevent journalists from embracing it. To answer these questions, the study draws on a combination of semi-structured interviews with investigative journalists and open data experts, case studies, and qualitative content analysis. In the final section, I discuss the existing barriers and provide guidelines on how to make investigative data journalism stronger in Russia.”

Research: “News bot for the newsroom: how building data quality indicators can support journalistic projects relying on real-time open data”

This is a research paper that was presented at the Global Investigative Journalism Conference 2017 Academic Track, which IJEC organized and covered.

Laurence Dierickx from the Université Libre de Bruxelles compares quality assessment models for data and their journalistic implications. Utilizing these models, she analyzes the data quality of a case study, namely an automated news generator that is based on air quality data.

“This paper proposes a conceptual framework to assess data quality with a combination of deterministic and empirical quality indicators. If data quality is a multidimensional concept, the object is here to establish how to fit the needs of journalistic projects. Formal quality indicators are essentials when data are collected and/or automated. We can call it the technical challenge. Empirical indicators are also essentials regarding professional practices. We can call it the journalistic challenge. This part of the paper also demonstrates how and why data quality literacy is able to meet and to support journalistic requirements.”

Research: “Data-driven journalism: Visualizing the lie versus revealing the truth”

This is a research paper that was presented at the Global Investigative Journalism Conference 2017 Academic Track, which IJEC organized and covered.

University professor and database journalism specialist Milagros Salazar researches the role of data in journalism, its potentials and limits.

“Journalism is full of data, but not everything is data journalism. There is a difference between using data and establishing a methodology in journalistic research that has, as a fundamental aspect, the organization, analysis and verification of data to find a real story.

But data alone are not enough. It is important to verify them and put a human face on them in order to find a real story to tell your audience. If data are not tested against the situation “on the ground”, there is a danger that they will show us lies, instead of helping us tell the truth in order to help people take better decisions for their lives.”