Adegboyega Ojo, of National University of Ireland, and Bahareh Heravi, of University College Dublin explore what characterises good data stories and how different technologies are being combined to create these stories.
The study analysed 44 cases of award-winning data journalism work, comprising winning entries of the Global Editors Network’s (GEN) Data Journalism Award from 2013 to 2016. The authors characterised each of the 44 cases and then determined types of these stories and the nature of technologies employed in creating them.
The results show that seven types of data stories characterise the 44 winning projects:
- Refute claims
- Reveal unintended consequences
- Reveal information of personal interest
- Enable deeper understanding of a phenomenon
- Reveal anomalies and deficiencies in systems
- Track changes in systems
- Reveal information about an entity in increasing levels of details
A quarter of the stories were categorised as explaining a phenomenon for deeper understanding type. Results also reveal that web development and publishing, data analysis and data visualisation are the core technologies needed in creating successful data stories.
The article “Patterns in Award Winning Data Storytelling: Story Types, Enabling Tools and Competences” is published by Digital Journalism and it can be found here (abstract is public).
Picture: Data Represented in an Interactive 3-D Form by Idaho National Laboratory, licence: CC BY 2.0