There is a tremendous amount of data spread across the web, stored in databases, and contained in maps that can be turned into an integrated semantic network of data, called a knowledge graph. Exploiting the available data to build knowledge graphs is difficult due to the heterogeneity in the types of sources, scale in the amount of data, and noise in the data.
In this talk I will present techniques we have developed for turning this data into knowledge graphs, including extracting data from both text and image sources, aligning the data to a common terminology, linking the data across sources, and querying the resulting knowledge graphs. I will describe two applications of these techniques: (1) a knowledge graph built from historical USGS topographic maps to analyze changes in the built environment and (2) a knowledge graph built from online sources about satellites and space systems in orbit to continuously monitor these systems.
Craig Knoblock's USC profile page
Geospatial Data Science Speaker Series
