Many of the systems studied by scientists evolve through time and space, like diseases spreading through a population, weather fronts rolling across a continent, and solar flares churning the atmosphere. A paper, part of a special series on what’s termed “spatial computing,” argues that understanding these processes will necessarily require computing systems to have a structure that reflects the corresponding spatial and temporal limits. According to its authors, the spatial nature of the systems being studied is reflected in everything from data gathering to its processing and the visualization of the results. So, unless we engineer the computing systems to handle spatial issues, we’re not going to have very good results.

It would be easy to dismiss spatial computing as a buzzword, except the authors provide concrete examples that demonstrate spatial issues do play a major role in scientific computing. Unfortunately, they also demonstrate that they play several roles, some of them largely unrelated to each other; as a result, the spatial tag ends up getting applied to several unrelated problems, which dilutes the message to an extent.

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