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This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
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This platform aims to realize data storage, data management, data analysis, data sharing and data citation traceability of various data sets in the field of Humanities and Social Sciences of East China Normal University.
Country
Geoscientific Data & Discovery Publishing Center (GDD) is based on the geological scientific data generated globally, establishing policies and systems for the scientific data publishing, absorbing the concepts and methods of international open data, and joint Digital Object Unique Identifier-DOI registration agencies to provide standard data reference formats and permanent access address for data references, doing publishing through the Internet platform, which combines innovation and advance. GDD mainly includes data descriptor and entity data publishing. The data papers describe entity data and corresponding metadata information. The entity data includes common shared data such as geographic information, geologic maps, and databases, and also includes multiple data types, such as documents, archive records, data forms and other multimedia formed during geological work, various data-centric applications, database interface services, and typical data services.
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The National Center for Forestry and Grassland Genetic Resources (Forestry and Grassland Repository) consists of a series of in situ and ex situ repositories and ex situ repositories, including 15 in situ repositories, 137 ex situ repositories and 3 facility repositories (attached), all of which are recognized by the Seedling Department of the State Forestry and Grassland Administration or the National Forestry Germplasm Resource Platform to collect and preserve forest, grass, flower, bamboo and rattan germplasm resources, and to establish a big data system through standardization, digitization. The purpose of the Forestry and Grassland Resource Bank is to strengthen the germplasm resources of forests, grasses, flowers, bamboos and rattan. The purpose of the Forestry and Grass Resource Bank is to strengthen the collection and preservation of forestry germplasm resources and open sharing, and to promote sustainable use; the objective is to use ultra-low temperature freezing, genomics, artificial intelligence and other high technology to carry out long-term preservation, accurate identification and in-depth exploration of germplasm resources, and to achieve safe preservation and efficient use of germplasm resources. The Forestry and Grassland Resource Bank undertakes the rendezvous of scientific and technological projects in the forestry germplasm resource category. By building an integrated sharing service platform for germplasm resource production, academia and research, it improves the innovation and exploitation capacity of forestry germplasm resources, supports major national needs in scientific research, ecological construction and economic development, promotes the docking of resources and needs, and facilitates the use of resources and the transformation of results. It realizes information and physical sharing, so that forest germplasm resources can be safely preserved and scientifically utilized.
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The National High Energy Physics Science Data Center (NHEPSDC) is a repository for high-energy physics. In 2019, it was designated as a scientific data center at the national level by the Ministry of Science and Technology of China (MOST). NHEPSDC is constructed and operated by the Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences (CAS). NHEPSDC consists of a main data center in Beijing, a branch center in Guangdong-Hong Kong-Macao Greater Bay Area, and a branch center in Huairou District of Beijing. The mission of NHEPSDC is to provide the services of data collection, archiving, long-term preservation, access and sharing, software tools, and data analysis. The services of NHEPSDC are mainly for high-energy physics and related scientific research activities. The data collected can be roughly divided into the following two categories: one is the raw data from large scientific facilities, and the other is data generated from general scientific and technological projects (usually supported by government funding), hereafter referred to as generic data. More than 70 people work in NHEPSDC now, with 18 in high-energy physics, 17 in computer science, 15 in software engineering, 20 in data management and some other operation engineers. NHEPSDC is equipped with a hierarchical storage system, high-performance computing power, high bandwidth domestic and international network links, and a professional service support system. In the past three years, the average data increment is about 10 PB per year. By integrating data resources with the IT environment, a state-of-art data process platform is provided to users for scientific research, the volume of data accessed every year is more than 400 PB with more than 10 million visits.
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The Open Archive for Miscellaneous Data (OMIX) database is a data repository developed and maintained by the National Genomics Data Center (NGDC). The database specializes in descriptions of biological studies, including genomic, proteomic, and metabolomic, as well as data that do not fit in the structured archives at other databases in NGDC. It can accept various types of studies described via a simple format and enables researchers to upload supplementary information and link to it from the publication.
In order to meet the needs of research data management for Peking University. The PKU library cooperate with the NSFC-PKU data center for management science, PKU science and research department, PKU social sciences department to jointly launch the Peking University Open Research Data Platform. PKU Open research data provides preservation, management and distribution services for research data. It encourage data owner to share data and data users to reuse data.
The WDC is concerned with the collection, management, distribution and utilization of data from Chinese provinces, autonomous regions and counties,including: Resource data:management,distribution and utlilzation of land, water, climate, forest, grassland, minerals, energy, etc. Environmental data:pollution,environmental quality, change, natural disasters,soli erosion, etc. Biological resources:animals, plants,wildlife Social economy:agriculture, industry, transport, commerce,infrastructure,etc. Population and labor Geographic background data on scales of 1:4M,1:1M, 1:(1/2)M, 1:2500, etc.