Data journalism is about journalists making news or stories based on data. We live in an information explosion age. Big data brings great opportunities to journalism and adds the value of accuracy and objectivity.
Big data has 4V characters: Volume, Velocity, Variety and Value.
Data journalism needs to have open data and open source available for people to mine, analyse, visualise data and map data and tell stories.
As the guideline from Data Journalism Handbook indicates, ‘Data can be the source of data journalism, or it can be the tool with which the story is told – or it can be both’. We should be open to this quantitative tool but watch out how reliable the source is and how it can shape the news.
Gathering data, interpreting them and crafting emotional stories on the basis of facts is the process of data journalism working on the endless expansion of information.
Image source: http://onmedia.dw-akademie.de/english/?tag=investigative-journalism
If data is improperly managed and interpreted, journalists may lose the direction and feel trapped in the data jungle.
Limitations of data journalism:
- The source of data is not always reliable as it could be from anywhere. Without careful research and selection, it may mislead the public;
- Heavily relying on data may lead to a lack of deep analysis as some aspects of news or stories cannot be assessed by facts or figures;
- If data news becomes a new type of journalism and other news was to follow this format, creativity or humanity would be lost;
- It’s not an ideal method to tell an interesting story and to make it lively.
Data journalism becomes an important part of journalism, in particular areas, such as investigative journalism or analysis journalism, but it’s not the future of journalism. It cannot change the dynamic and principle of journalism and it should not.
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