An open source framework to add spatial extent and geospatial visibility to Big Data

Advancement in the field of computing and remote handheld devices has made the process of collecting geospatial data easy. Most of the time researchers and scientists have easy access to these data as well. However, the process of extracting and processing a large volume of data from several sources can be very time consuming and difficult. In most cases scientists rely on expensive proprietary software [1]. This paper discusses how Computational Scientists at Oak Ridge National Laboratory are extracting, normalizing, and processing millions of geospatial data points from multiple data sources and integrating them into a common data format which helps user to find and access these data using a flexible visualization-based user interface.