After extensive research I’ve come to this conclusion: Across all business small to multinational, governments at all levels, regulators, and NGOs alike…
What matters most, because it’s vital, is that we very effectively communicate with data, numbers, facts and empirical evidence.
What’s at stake? Well it’s the quality of our corporate decisions, natural environments, public policies and laws; along with our collective ability to best avoid or mitigate risks and improve outcomes on a global scale. Important matters.
The field and technologies of data visualization and visual analytics will be a critically central part of any optimizing analytical digital solution.
But, in my opinion, the current data visualization tools and solutions have a few nagging deficiencies:
- Portraying Data as simple misses important nuances and risks present in most data
- While you can select from a Vast Array of Visualization Types or templates, that’s not sufficient to make a visualization successful.
- And the industry leading practice guidance, Just approach it like Storytelling, is basically inadequate.
We have some different ideas that ultimately point the technologies in this direction:
Dynamic, interactive and broadly-shared data visualizations will have artificial intelligence features (which are transparent and governed) supporting adaptive visual analytics, as well as the people using them.
- Our approach recognizes that data are highly complex, elastic, malleable; and uses these metadata to support deeper visual analytics.
- It holds that at a fundamental level we can speak to core components or aspects of the data. And we should design to those, first and foremost.
- It uncovers the enormous value in data visualization that comes from the ability to easily understand what you’re seeing– vs. not– and be able to speak to it directly and accurately.
- It’s ultimately a platform for dynamic, open dialogue between the builders and consumers of data.
The call to action is straightforward: if you have an interestingly difficult analytical, empirical problem, where our ideas on data visualization seem aligned and compelling, then contact us.
A data visualization is not a story, and you shouldn’t be merely storytelling.
On first principles, a truly effective data visualization needs to be much more a structured discussion.
In it you navigate a cloud of interrelated ideas, facts, observations, beliefs and conclusions, shared among many colleagues (or citizens) with defined goals and measured outcomes.
Then the awareness and understanding of any complex problem, as well as its range of effective solutions, all evolve within a shared, transparent and visualized analytical environment.
This is not a story. It’s actually my vision.
— Ross Waring
(p.s., Visualize more.)