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Layering the World


Microscopes have advanced so far since their inception, they may soon be able to see the small scale in almost infinite detail. But the large scale? It seems much easier to visualize—look up at the sky—but when big, complex data gets thrown into the mix, that may not be the case. The sky is blue, sure, but what impact does that have?

To help answer questions such as those, Hendrik Hamann, research manager for Physical Analytics, IBM Research, and colleagues are working on what they call a “macroscope.” This technology will allow users to employ, for example, satellite imagery of the earth, climate conditions, Internet of Things (IoT) data, population rates and water conditions to determine when and where to grow what types of crops.

“To conduct space and time analyses, you need access to all of these different layers of information at the same time and in the same space. That’s exactly what the macroscope is promising.”
—Hendrik Hamann, research manager for Physical Analytics, IBM Research

And this is only the beginning. By layering geospatial and assorted other data, big-picture questions will soon be answered on a level almost as detailed as what a microscope can expose, all easily searchable and discoverable.

IBM Systems Magazine (ISM): Information in the virtual world has already been pretty well indexed and made. How would a similar approach to the physical world work?
Hendrik Hamann (HH):
We can search 45 billion webpages in less than 0.5 seconds because we’ve done a fantastic job of indexing available digital data, including data from social networks and relations. The macroscope is aiming to do this for data from the physical world, which is generally spatiotemporal data. It allows you to bring information together that’s in space and time. So you can pretty easily find everything on the web today, including locations that are close to where you live, for example.

But it’s a completely different task to ask where you’d like to live. You can see in a magazine the 10 best places in America to live, but that’s very nonsystematic. So you have to develop a profile: “I want to live right where there are a lot of Italian restaurants, where it’s not too hot, it’s not too cold but I would still like a little bit of the seasons.” Then you would search a large spatiotemporal data set. With the macroscope, we’ll make all of that data much more searchable and discoverable.

ISM: Stupid question, but what makes it so difficult to index space and time?
Anything in the physical world happens in either space and/or time. That may sound like a trivial thing, but when you really start thinking about information in space and time, it’s not that easy. For example, with space, there are different map projections because the earth is neither round nor spherical, etc. And if you want to link things in space, things are moving. Continental plates are moving in space and moving in time, so actually making links in space and time is very complex.

Data size creates another issue. Global weather data, for example, represents tens of terabytes every day. That makes it very difficult to make information such as this searchable and discoverable. We have to make big progress towards digitizing the physical world through the IoT and then make that information much more accessible, discoverable, etc.

Jim Utsler, IBM Systems Magazine senior writer, has been covering the technology field for more than a decade. Jim can be reached at



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