Geoinformatics Facilities Support: Integrated Data Collections for the Earth & Ocean Sciences: The Marine Geoscience Data System and the Geoinformatics for Geochemistry Program

Lead PI: Dr. Kerstin A. Lehnert , Dr. Suzanne M. Carbotte , Vicki Ferrini , , Stephen Richard, Karin Block, William Ryan

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

October 2010 - September 2017
North America ; New York City, NY ; New York
Project Type: Facilities & Operations

DESCRIPTION: This Cooperative Agreement creates a community-driven facility that consolidates a number of essential cyberinfrastructure activities in the solid-earth geosciences at the Lamont Doherty Earth Observatory of Columbia University. It includes data repositories; author attribution schema; data management, discovery, and visualization tools; web portals and services; and the development and implementation of a sample unique-identifier registration system and database interoperability and metadata standards. The project also includes the creation of geoscience education and outreach modules and workshops. Goals of the facility are to serve the data management and discovery needs of the geoscience community and to provide direct public accessibility to NSF-funded data sets and associated data products. To achieve these goals, the collected activities are overseen by an external advisory structure of users and domain scientists in the geoinformatics, geophysics, igneous petrology, geochemistry, sedimentology, hydrothermal vent fluid, and polar geoscience communities and who work in concert with NSF to best serve community needs and monitor project performance. The broader impacts of the resulting facility and its activities are broad and far-reaching in terms of building infrastructure for science and education in the solid-earth geosciences. The resulting infrastructure and unified data submission procedures and standards will significantly advance the field of geoinformatics and provide essential tools for discovering data and combining disparate datasets such that more complex scientific problems can be tackled by providing a means to efficiently collect and view and model multiple datasets. It also provides an important educational tool for students by allowing them to explore large amounts of data in creative ways.