EarthCube
Current Projects
GeoSCIFramework: Scalable Real-time Streaming Analytics and Machine Learning for Geoscience and Hazards Research. This project develops a real-time processing system capable of handling a large mix of sensor observations using automated detection of natural hazard events using machine learning, as the events are occurring. A four-organization collaboration (UNAVCO, University of Colorado, University of Oregon, and Rutgers University) develops a data framework for generalized real-time streaming analytics and machine learning for geoscience and hazards research. This work will support rapid analysis and understanding of data associated with hazardous events (earthquakes, volcanic eruptions, tsunamis).
Past Projects
UNAVCO collaborated with a number of National Science Foundation (NSF) GEO-funded institutions on an NSF EarthCube project, led by IRIS, entitled Deploying Web Services Across Multiple Geoscience Domains. This EarthCube Building Blocks project extended the promotion of simple web services to simplify the task of discovering, accessing and using data from multiple sources. This building block is an effort to engage EarthCube cyberinfrastructure in developing, establishing and adopting international standards to allow geoscientists to focus on science and increase productivity. UNAVCO is specifically developing web services for GPS timeseries, station metadata, seismic and borehole strainmeter data, and other related data and data products.
Enabling Scientific Collaboration and Discovery through Semantic Connections, an EarthCube Building Blocks program NSF award, demonstrated how new technologies, can enhance the coordination and organization of scientific virtual organizations and their products, thereby accelerating the pace of scientific discovery and innovation. The project was a collaborative effort between UNAVCO (UNAVCO Abstract #1440213), the University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR) and Cornell University. VIVO is an open source semantic web application populated with researcher information that was developed at the Cornell University Library. Our project is focusing on two scientific case studies to connect researchers with data and tools: 1. Geodetic research and data supported by UNAVCO and 2. Atmospheric and polar research and data supported by the Earth Observing Laboratory’s Bering Sea Project.
Last modified: 2019-12-24 02:13:00 America/Denver