The network elements of the ECOGEO RCN reach across diverse communities of ocean scientists, geoscientists, computer scientists and bioinformaticians, and will forge new cross-disciplinary connections. Although the scientific goals of the proposed ECOGEO community network are diverse, common challenges and requirements for big data analyses be identified across this broad community. This project will provide new solutions and ideas that reach beyond disciplinary boundaries, since the challenges of rich omic datasets share commonalities across areas as diverse as soil science, oceanography, geobiology and studies of the human microbiome. Best practices and use case scenarios developed in this project will integrate across challenges of diverse science domains, and provide well documented approaches for omic data management and analyses, that will serve as models and test cases for new cyberinfrascructure systems. These efforts will impact not only ocean scientists and geobiologists, but also other allied areas that use the same approaches, that range from environmental assessment to human health.

Inexpensive sequencing has facilitated the generation of billions of environmental DNA sequences, and allied techniques to survey gene expression (metatranscriptomics) and protein expression (metaproteomics) are advancing as well. The large and complex environmental omic datasets now present major challenges to the ocean and geoscience communities. These omic datasets are diverse, complex, and exponentially expanding, and require the construction, curation, and query of diverse federated databases, as well as development of shared interoperable, big-data capable analytical tools. To help address these current big data challenges, this project establishes a virtual network called EarthCube Oceanography and Geobiology Environmental Omics Research Coordination Network (ECOGEO RCN), that will foster collaborations, communication, innovation, and education in omic data management and analyses in the oceanography and geobiology communities. The effort will identify and communicate needed data standards, sharing and access mechanisms and analytical strategies across the broader community of ocean and geosciences. Major outcomes of ECOGEO RCN will be: 1)Establishment of a virtual network that coordinates collaboration and communication in omics, data sharing and analyses; 2)Training of a cyber-savvy generation of ocean and geo science graduate students, postdocs and young professionals in the rapidly evolving environmental omics and bioinformatics field. 3)Identification and elaboration of environmental omic data standards, ontologies, sharing mechanisms, and analytical strategies; 4)Development of use case scenarios that will inspire creation of a new palette of user friendly inter-operative community data management, analytical and visualization tools for oceanography and geobiology omic science and beyond.

The establishment of the ECOGEO RCN will provide a collection of online resources to enable the access, management and discovery of oceanographic and geobiology omic data, metadata, analysis tools, methodologies, and other user-driven needs. An EarthCube hosted ECOGEO-Wiki will serve as open forum for network participants to share content and link to data repositories, models, and tools. The ECOGEO centralized network and web-based portal will promote better communication within and between ECOGEO microbial oceanography and geobiology scientists and the broader scientific community. This will enable greater access and organization of large and heterogeneous datasets, greater efficiencies in scientific discovery, and broader collaborations based on both survey and experimental data. The overall result will be to facilitate access and use of existing and rapidly accumulating new omic datasets for a wide range of ocean science and geoscience users, to observe measure and model community composition, biological and biogeochemical activities and ecosystem structure and function from ocean surface waters to the deep subsurface.

Project Start
Project End
Budget Start
2014-09-01
Budget End
2017-02-28
Support Year
Fiscal Year
2014
Total Cost
$359,995
Indirect Cost
Name
University of Hawaii
Department
Type
DUNS #
City
Honolulu
State
HI
Country
United States
Zip Code
96822