The whole world is now like a stock market. Just as financial markets have been generating massive volumes of real time data, now there are real time data feeds that describe the rest of the world - everything from weather patterns to air and automobile traffic to electrical power consumption and consumer purchasing activity.

On one hand this flood of data can make us feel overwhelmed and unable to cope. On the other hand, it can be our ticket to the next level of understanding and living in our world.

We need a fundamental new approach to that dry and often boring activity we presently call business intelligence (BI). For the most part, we are still using quaint two dimensional displays such as line graphs, bar charts and scatter plots to visualize data. These techniques date from two hundred years ago when data was scarce, collection of data happened only occasionally, and we had lots of time to dissect and analyze the data because things didn't change that fast. That isn’t the case anymore and these two dimensional techniques just don’t cut it. Literally, by the time one of these displays is created, it is obsolete; the real-time data it is trying to represent has changed.

So the question is how to we display massive real-time data flows and do so in a way we humans can understand? Think about this: which of our five senses has the largest bandwidth? Which one do we use every waking moment to collect, assess, orient and react to a continuous flow of real-time data? The answer is, of course, our sense of sight. And from the time we first learn to see as babies, we organize sight data into 3D spaces and we identify and monitor objects in those spaces by using characteristics such as their size, shape and position and the rate of change in these characteristics.

In order to make sense out of and respond effectively to real-time data flows, we need to organize and display this data using the exact same principles that our brain uses when it organizes and displays sight data.

Okay, you say, that’s a fascinating abstract concept. But so what? Why do I care?

Here’s an example of using moving 3D displays to understand real world data in real-time. Let’s talk about using it to solve some really big problems – like global warming and environmental sustainability (if it works for these problems it will work for lots of other problems too). We know we have to do something about all this; but the scope of the undertaking is overwhelming; and the amount of data is beyond comprehension. Yet we need all that data or we won’t know whether our efforts are creating the desired results (until it’s too late). We need continuous data feedback loops (planetary data feedback loops) to tell us if we are on track and to enable us to make mid-course corrections as needed.

After much posturing, the nations of the world have just agreed to start the next round of negotiations to deal with greenhouse gases and global warming. These negotiations promise to be exhausting, prolonged, and maybe even fatally flawed by clever negotiating and creative data interpretation. We can be sure that the best experts that can be found will present and spin all sorts of data to prove or disprove all sorts of points. How are we ever going to come up with something that has a chance of actually working?

If we apply the principle of making the world visible in order to understand it, then we need to do two things. First we

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