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Found 24 result(s)
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Based on the needs of national scientific and technological innovation for laboratory animal resources, we use various methods such as foreign introduction, domestic collection, independent research and development, and protocol conservation to collect, integrate, and optimize laboratory animal resources. The resource library now preserves more than 200 varieties and strains in four categories, including mice, rats, guinea pigs, and rabbits, including routine laboratory animals, genetically modified animal models, and animal models for disease. The predecessor of the resource bank was the National Rodent Laboratory Animal Seed Center (Guoke Cai Zi [1998] No. 010), established in 1998 and based on the Laboratory Animal Resources Research Institute of the Chinese National Academy of Food and Drug Administration.
The National Science Digital Library provides high quality online educational resources for teaching and learning, with current emphasis on the sciences, technology, engineering, and mathematics (STEM) disciplines—both formal and informal, institutional and individual, in local, state, national, and international educational settings. The NSDL collection contains structured descriptive information (metadata) about web-based educational resources held on other sites by their providers. These providers have contribute this metadata to NSDL for organized search and open access to educational resources via this website and its services.
The South African Environmental Observation Network (SAEON) Open Data Platform (ODP) is a metadata repository that facilitates the publication, discovery, dissemination, and preservation of earth observation and environmental data in South Africa. SAEON is a long-term environmental observation and research facility of the National Research Foundation (NRF).
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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.
Country
Standard, reference material is used for measurement process control and reliability evaluation of measurement results, and plays a key role in important fields such as food safety, international and domestic trade, medicine and health, and environmental monitoring. In order to realize the efficient use and sharing of reference material resources in the whole society, the Institute of Chemistry of China Institute of Metrology (formerly the National Reference Material Research Center), with the support of the Ministry of Science and Technology, launched the "National Reference Material Information Service" at the end of 2003.
EarthWorks is a discovery tool for geospatial (a.k.a. GIS) data. It allows users to search and browse the GIS collections owned by Stanford University Libraries, as well as data collections from many other institutions. Data can be searched spatially, by manipulating a map; by keyword search; by selecting search limiting facets (e.g., limit to a given format type); or by combining these options.
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 Avian Knowledge Network (AKN) is an international network of governmental and non-governmental institutions and individuals linking avian conservation, monitoring and science through efficient data management and coordinated development of useful solutions using best-science practices based on the data.
NKN is now Research Computing and Data Services (RCDS)! We provide data management support for UI researchers and their regional, national, and international collaborators. This support keeps researchers at the cutting-edge of science and increases our institution's competitiveness for external research grants. Quality data and metadata developed in research projects and curated by RCDS (formerly NKN) is a valuable, long-term asset upon which to develop and build new research and science.
Country
The National Microbial Resource Center (NMRC) is an important part of the national science and technology resources sharing service platform, responsible for the research, conservation, management and sharing of national microbial strain resources, ensuring the strategic security and sustainable use of microbial strain resources, and providing support for scientific and technological innovation, industrial development and social progress. The main tasks of the NMRC are: to collect, organize and preserve microbial strain resources around national needs and scientific research; to undertake the task of remitting, organizing and preserving strain resources resulting from the implementation of science and technology projects; to be responsible for the development and improvement of microbial strain resource standards, and to standardize and guide the development of microbial strain resources in various fields. The company is responsible for the development and improvement of microbial strain resource standards, standardizing and guiding the protection and utilization of microbial strain resources in various fields; building and maintaining the national strain resource online service system, and carrying out social sharing of physical and information resources of strains; developing key common technologies, creating new resources, and carrying out customized services according to innovative needs; carrying out scientific popularization for the society; carrying out international exchange and cooperation on strain resources, participating in relevant international academic organizations, and safeguarding national interests and Security
A planetary-scale platform for Earth science data & analysis. Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. Scientists, researchers, and developers use Earth Engine to detect changes, map trends, and quantify differences on the Earth's surface.
The NCEAS Data Repository contains information about the research data sets collected and collated as part of NCEAS' funded activities. Information in the NCEAS Data Repository is concurrently available through the Knowledge Network for Biocomplexity (KNB), an international data repository. A number of the data sets were synthesized from multiple data sources that originated from the efforts of many contributors, while others originated from a single. Datasets can be found at KNB repository https://knb.ecoinformatics.org/data , creator=NCEAS
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
Country
INRAE is the world’s first organisation specialized on agricultural, food and environmental sciences. Data INRAE is offered by INRAE as part of its mission to open the results of its research. Data INRAE will share research data in relation with food, nutrition, agriculture and environment. It includes experimental, simulation and observation data, omic data, survey and text data. Only data produced by or in collaboration with INRAE will be hosted in the repository, but anyone can access the metadata and the open data.
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.
<<<!!!<<< 2020-08-28; the repository is no longer available >>>!!!>>> The South African Data Archive promotes and facilitates the sharing of research data and related documentation of computerised raw quantitative data of large scale regional, national and international research projects mainly in the humanities and social sciences. It makes these datasets available to the research community for further analysis, comparative studies, longitudinal studies, teaching and decision-making purposes.