And it lets us look at inputs as well as outputs. For instance, let's say we color code our emissions, and our model shows an air pollution source out in the desert where we know there isn't one. We can spot this problem much easier with the visualization than we could by looking through pages and pages of numbers. Due to this rapid analysis capability, the model is a fairly accurate representation of the processes that produce air pollution. You can put emissions into it, and it predicts air quality.
Lighter colors are higher concentrations.
Lighter colors are higher concentrations. Jason Ng, senior research programmer with NCSA's Software Development Group, continues to develop NCSA X DataSlice. He says that newer versions of the software will be much more powerful. Future development will involve linking up the functionality of X DataSlice with the collaboration tools that allow two people from across the country to work interactively on the same data at the same time. Both can rotate the visualization, change color, write notes to each other, etcetera.