Is What You See, What You Get? Geospatial Visualizations Address Scale and Usability AashishChaudharyandJeffBaumes U nlimited geospatial information now is at everyone’s fingerti ps with the proliferation of GPS-embedded mobile devices and large online geospatial d atabases. To fully understand these data and make wise decisions, more people are turnin g to informatics and geospatial visualization, which are used to solve many real-world proble ms. To effectively gather information from data, it’s critical to ad dress scalability and intuitive user interactions and visualizations. New geospatial analysis and vi sualization techniques are being used in fields such as video analysis for national defense, urb an planning and hydrology. Why Having Data Isn’t Good Enough Anymore 

People are realizing that data are only useful if they can find t he relevant pieces of data to make better decisions. This has broad applicability, from findi ng a movie to watch to elected officials deciding how much funding to allocate for an aging bridge. Information can easily be obtained, but how can it be sorted, organized, made sense o f and acted on? The field of informatics solves this challenge by taking large amounts of d ata and processing them into meaningful, truthful insights. In informatics, two main challenges arise when computers try to condense information down to meaningful concepts: disorganization and size. Some inform ation is available in neat, organized tables, ready for users to pull out the needed piece s, but most is scattered across and hidden in news articles, blog posts and poorly organized lists. 

Researchers are feverishly working on new ways to retrieve ke y ideas and facts from these types of messy data sources. For example, services such as Go ogle News use computers that constantly "read" news articles and posts worldwide, and the n automatically rank them by popularity, group them by topic, or organize them based on what the computer thinks is important to viewers. Researchers at places such as the Unive rsity of California, Irvine, and Sandia National Laboratories are investigating the next appro aches to sort through large amounts of documents using powerful supercomputers. The other obstacle is the sheer volume of data. It’s difficult t o use informatics techniques that only work on data of limited size. Facebook, Google and Twitt er have data centers that constantly process huge quantities of information to deliver ti mely and relevant information and advertisements to each person currently logged on.