Key points by Ioanna Georgia Eskiadi
Data journalism involves a kind of journalism which employs data. Data… digital files usually numbers in spreadsheet format and usually it includes the production of some kind of visualization for example an infographic. Data Journalism is obtaining, reporting on, curating, publishing data in the public interest. Just the discovery of interesting data does not constitute data journalism.
Data journalism can be defined as the process of extracting information from data, writing articles, embedding visualization in the articles that help readers understand the significant of the story or allow them to pinpoint data that relate to them. Data journalism has been developed due to the availability of tools that manage data, of open data and visualization software/online services. Also, people trust more articles that are based on data. The five stages in the work flow of data journalism are data compilation, data cleaning, data understanding, data validation, data visualization and article writing. In every stage journalist uses different software and tools to calculate and make readable various things.
The two paths of conducting data journalism refer to the one based on individual tools with no code skills necessary and the other one based exclusively on coding like Python, R, Jupiter notebook. Workbench data combines features from both approaches. It can be employed by journalists with no coding skills and with coding skills. It’s free and supports group work.
The 5th Thessaloniki International Summer Academy on Media is organized by School of Journalism and Mass Communications of Aristotle University Thessaloniki (AUTh), Jean Monet of European Union Public Diplomacy along with other partners under the title: “New trends in Media and Journalism: Turning crisis into opportunity”.
Special emphasis is given on the topics:
1. Disinformation, Science Journalism / News Literacy
2. Crisis Communication
3. New business models in Media Organisations