![]() Our overall goal is figuring out how we can take all of this data that’s in different formats, and put it all together so that the machines can learn from it.” Sometimes it’s images, and sometimes it’s time-series data with a location dimension. “We’re working with data from lots of different sources and maps. ![]() “What we do is build machine learning models that can leverage and work well with spatial data,” said Yao-Yi Chiang, an associate professor of computer science and engineering who runs the UMN Knowledge Computing Lab. One of their current projects has turned nearly 60,000 historical maps into unique, relevant information that benefits research in a wide range of fields including demography, landscape ecology, biogeography, history, and economics. Researchers in the University of Minnesota College of Science and Engineering (CSE) are working to harness this data not only to glean information from it, but also to transform it into tools that can solve real-world problems. Even the products we buy at the store include labels or a barcode embedded with the manufacturer or brand’s address. Everywhere you set foot has a unique set of GPS coordinates. When you take a photo with your smartphone, it records the location the photo was taken. Spatial data-or information with a location attached to it-is all around us. Technology from Associate Professor Yao-Yi Chiang’s research team could reduce human labor and speed up map analyses
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