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Found 19 result(s)
E-RA provides a permanent managed repository and knowledgebase for secure storage of metadata and data from Rothamsted's Long-term Experiments, the oldest, continuous agronomic experiments in the world. Together with the accompanying meteorological records, associated documentation and sample archive, it is a unique historical record of experiments that have been measured continuously since 1843. e-RA provides comprehensive descriptions of Rothamsted's long-term experiments including Broadbalk Wheat, Park Grass Hay, Hoosfield Barley, Rothamsted and Woburn Ley Arables, and Long-term Liming. e-RA maintains long-term routine data collections including crop yields, quality traits, agronomic management, soil chemistry, disease, and botanical diversity. The experiments are available as a research infrastructure to scientists and scientists are encouraged to deposit any new data generated with e-RA.
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In the framework of the Collaborative Research Centre/Transregio 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’ (CRC/TR32, www.tr32.de), funded by the German Research Foundation from 2007 to 2018, a RDM system was self-designed and implemented. The so-called CRC/TR32 project database (TR32DB, www.tr32db.de) is operating online since early 2008. The TR32DB handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne, Bonn, Aachen, and the Research Centre Jülich) and research fields (e.g. soil and plant sciences, hydrology, geography, geophysics, meteorology, remote sensing). The data is resulting from several field measurement campaigns, meteorological monitoring, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected in the TR32DB.
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
Within WASCAL a large number of heterogeneous data are collected. These data are mainly coming from different initiated research activities within WASCAL (Core Research Program, Graduate School Program) from the hydrological-meteorological, remote sensing, biodiversity and socio economic observation networks within WASCAL, and from the activities of the WASCAL Competence Center in Ouagadougou, Burkina-Faso.
GRID-Geneva is a unique platform providing analyses and solutions for a wide range of environmental issues. GRID-Geneva serves primarily the needs of its three institutional partners - UNEP, the Swiss Federal Office for the Environment (FOEN) and the University of Geneva (UniGe) - which are linked by an ongoing, multi-year “Partnership Agreement”, along with other local-to-global stakeholders. GRID-Geneva is also a bilingual English and French centre and the key francophone link within the global GRID network of centres. GRID-Geneva is a key centre of geo-spatial know-how, with strengths in GIS, IP/remote sensing and statistical analyses, integrated through modern spatial data infrastructures and web applications. Working at the interface between scientific information and policy/decision-making, GRID-Geneva also helps to develop capacities in these fields of expertise among target audiences, countries and other groups.
SESAR, the System for Earth Sample Registration, is a global registry for specimens (rocks, sediments, minerals, fossils, fluids, gas) and related sampling features from our natural environment. SESAR's objective is to overcome the problem of ambiguous sample naming in the Earth Sciences. SESAR maintains a database of sample records that are contributed by its users. Each sample that is registered with SESAR is assigned an International Geo Sample Number IGSN to ensure its global unique identification.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
The Arctic Data Center is the primary data and software repository for the Arctic section of NSF Polar Programs. The Center helps the research community to reproducibly preserve and discover all products of NSF-funded research in the Arctic, including data, metadata, software, documents, and provenance that links these together. The repository is open to contributions from NSF Arctic investigators, and data are released under an open license (CC-BY, CC0, depending on the choice of the contributor). All science, engineering, and education research supported by the NSF Arctic research program are included, such as Natural Sciences (Geoscience, Earth Science, Oceanography, Ecology, Atmospheric Science, Biology, etc.) and Social Sciences (Archeology, Anthropology, Social Science, etc.). Key to the initiative is the partnership between NCEAS at UC Santa Barbara, DataONE, and NOAA’s NCEI, each of which bring critical capabilities to the Center. Infrastructure from the successful NSF-sponsored DataONE federation of data repositories enables data replication to NCEI, providing both offsite and institutional diversity that are critical to long term preservation.
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National ecosystem data bank (EcoDB) is a public professional scientific data repository supported by the National Ecosystem Science Data Center (NESDC) for researchers in ecology and related fields, which provides long-term preservation, publication, sharing and access services of scientific data. EcoDB provides services for both individual researchers and scientific journals. Individuals can use this repository to store, manage and publish scientific data, get feedback from others on the data, and discover scientific data shared by others through this repository. Journals can use the repository to gather, manage and review the supporting data of submitted paper. At the same time, journals can timely publish these supporting data according to their own data policies.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.
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Historical Climate Data (formerly: The National Climate Data and Information Archive - NCDC) is a web-based resource maintained by Environment and Climate Change Canada and the Meteorological Service of Canada. The site houses a number of statistical and data compilation and viewing tools. From the website, users can access historical climate data for Canadian locations and dates, view climate normals and averages, and climate summaries. A list of Canadian air stations and their meteorological reports and activities is also available, along with rainfall statistics for more than 500 locations across Canada. Users can also download the Canadian daily climate data for 2006/07. In addition, technical documentation is offered for data users to interpret the available data. Other documentation includes a catalogue of Canadian weather reporting stations, a glossary, and a calculation of the 1971 to 2000 climate normals for Canada. This resource carries authority and accuracy because it is maintained by a national government department and service. While the majority of the statistics are historical, the data is up-to-date and contains current and fairly recent climate data. This government resource is intended for an audience that has the ability and knowledge to interpret climatological data
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.