R-Storytelling in Dashboards
Susie Lu introduces Explanatory vs exploratory data visualisations:
- Explanatory = has a clear story (ex: most infographics or 'scrollytelling' websites you see)
- Exploratory = enable people to examine data in various ways and reach their own conclusions (ex: a dashboard)
Susie Lu argues Exploratory is not the same as not having a narrative. Rather, it's like a [[!Choose Your Own Adventure]] story with a branching narrative. The narrative may branch
Storytelling devices you can use:
- Setting the scene
- Introducing concepts over time
- Providing contrast
- Pushing the narrative towards a climax
- Branch the narrative based on the user's goal
- Provide different insights for different user needs
- Branch the narrative based on the type of data you have.
- Optimize your visualizations for different data scenarios.
- Users should want to come back to your dashboard whenever they need to answer a question with that data.
- Learn from game design and HUD as a mental model for a dashboard.
- Design for multiple visits (plays) with easily recognised features and tools.
- Clearly mark what you can interact with.
- Make it easy to save and share.
- Consider the user's 'inventory'. What tools do they need? Do they change over time? Do they persist?