Eager: Collaborative Research: EarthCube Building Blocks, Leveraging Semantics and Linked Data for Geoscience Data Sharing and Discovery

Lead PI: Dr. Suzanne M. Carbotte , , Robert A. Arko

Unit Affiliation: Marine and Polar Geophysics, Lamont-Doherty Earth Observatory (LDEO)

September 2013 - August 2015
North America ; United States
Project Type: Research

DESCRIPTION: This innovative project carries out exploratory research applying semantic technologies to support data representation, discovery, sharing, and integration between disparate geoscience data types and structures. It is a risky, high pay-off activity that, if successful, has the potential to transform our ability to discover, access, and use geoscience data in ways not possible at present. The goal of this research is to develop a prototype involving the data collections of some major NSF-funded Data Management Centers: IEDA and R2R at the Lamont Doherty Earth Observatory at Columbia University and BCO-DMO at the Woods Hole Oceanographic Institution. The effort is focused on making NSF-collected data for the ocean sciences and other associated datasets more easily and widely accessible and available to researchers and the public. Linked Open Data methodologies will be employed. Essential elements of this approach include the use of unique data identifiers to mark, link-to, and dereference specific data and details. Once the initial relationships are aligned, the new system can automatically infer new relationships between data and data locations. Goals will be to semantically integrate the data already available from the initially targeted data repositories in such a way that the approach can be scaled up to the whole of EarthCube, a new NSF initiative to develop a geoscience knowledge and data management system for the 21st Century. This project is a collaboration between ocean science researchers, computer scientists, and ocean data management centers from Maryland, Ohio, New York, and Massachusetts. Broader impacts of the work include building infrastructure for science and improving public accessablity to NSF-funded data collections