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Found 7 result(s)
The objective of this Research Coordination Network project is to develop an international network of researchers who use genetic methodologies to study the ecology and evolution of marine organisms in the Indo-Pacific to share data, ideas and methods. DIPnet was created to advance genetic diversity research in the Indo-Pacific by aggregating population genetic metadata into a searchable database (GeOME).
This interface provides access to several types of data related to the Chesapeake Bay. Bay Program databases can be queried based upon user-defined inputs such as geographic region and date range. Each query results in a downloadable, tab- or comma-delimited text file that can be imported to any program (e.g., SAS, Excel, Access) for further analysis. Comments regarding the interface are encouraged. Questions in reference to the data should be addressed to the contact provided on subsequent pages.
The Precipitation Processing System (PPS) evolved from the Tropical Rainfall Measuring Mission (TRMM) Science Data and Information System (TSDIS). The purpose of the PPS is to process, analyze and archive data from the Global Precipitation Measurement (GPM) mission, partner satellites and the TRMM mission. The PPS also supports TRMM by providing validation products from TRMM ground radar sites. All GPM, TRMM and Partner public data products are available to the science community and the general public from the TRMM/GPM FTP Data Archive. Please note that you need to register to be able to access this data. Registered users can also search for GPM, partner and TRMM data, order custom subsets and set up subscriptions using our PPS Data Products Ordering Interface (STORM)
GLOBE (Global Collaboration Engine) is an online collaborative environment that enables land change researchers to share, compare and integrate local and regional studies with global data to assess the global relevance of their work.
The HMAP Data Pages are a research resource comprising of information derived largely from historical records relating to fishing catches and effort in selected spatial and temporal contexts. The History of Marine Animal Populations (HMAP), the historical component of the Census of Marine Life, aimed to improve our understanding of ecosystem dynamics, specifically with regard to long-term changes in stock abundance, the ecological impact of large-scale harvesting by man, and the role of marine resources in the historical development of human society. HMAP data is also accessible through the Ocean Biogeographic Information System (OBIS): http://www.iobis.org/, see also: http://seamap.env.duke.edu/dataset
The MARGINS Data Portal was established in fall 2003 in response to a program call for a dedicated data system to facilitate open and timely exchange of data in support of the interdisciplinary science goals of the program. The Data Portal has been built with the primary goal of providing full cataloging, open access, and long-term preservation of data collected during MARGINS/GeoPRISMS programs. The backbone of the system is an expedition metadata catalog, which provides information on field programs (who, what, when and where), inventories of sensor data and samples, relevant metadata and the links to associated data files which reside either within the Data Portal or at distributed repositories. The system is designed to leverage all relevant existing data resources and provides a framework for a broader distributed data system.
EOL’s platforms and instruments collect large and often unique data sets that must be validated, archived and made available to the research community. The goal of EOL data services is to advance science through delivering high-quality project data and metadata in ways that are as transparent, secure, and easily accessible as possible - today and into the future. By adhering to accepted standards in data formats and data services, EOL provides infrastructure to facilitate discovery and direct access to data and software from state-of-the-art commercial and locally-developed applications. EOL’s data services are committed to the highest standard of data stewardship from collection to validation to archival.