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Found 8 result(s)
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The future of tropical forests matter to future climate. NGEE-Tropics is advancing model predictions of tropical forest carbon cycle responses to a changing climate over the 21st Century.
DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.
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The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
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.
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The India Environment Portal provides open access to information about environmental and developmental issues in India. The Portal aggregates and presents data from research institutions, government bodies, NGOs, universities, the mass media, and experts across various issues of environmental management.
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Attention! Data sets are not updated anymore. Please, visit the BonaRes Repositor​ium​ for new datasets. Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.