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Found 50 result(s)
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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.
The Integrated Catalogue (InK) of Mediathek of the Basel Academy of Art and Design (Hochschule für Gestaltung und Kunst Basel, HGK) hosts, collects, archives and makes available digital resources of HGK and its digital, special collections. It is available both to members of the Academy of Applied Sciences of Northwestern Switzerland (Fachhochschule Nordwestschweiz, FHNW) to which the HGK belongs and to the general public. In addition to data for internal university use (login area), there is a large amount of unrestricted, freely accessible content. The thematic focus is on contemporary art and design, art and design research, and topics related to the HGK. The sources cover a wide range of media: in addition to thesis and PDFs based documents, there are cluster objects, which assign several images, videos, audio and/or text files to a defined data set. The InK serves as an institutional repository for research data management and as a platform for hybrid publications.
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
The GRSF, the Global Record of Stocks and Fisheries, integrates data from three authoritative sources: FIRMS (Fisheries and Resources Monitoring System), RAM (RAM Legacy Stock Assessment Database) and FishSource (Program of the Sustainable Fisheries Partnership). The GRSF content publicly disseminated through this catalogue is distributed as a beta version to test the logic to generate unique identifiers for stocks and fisheries. The access to and review of collated stock and fishery data is restricted to selected users. This beta release can contain errors and we welcome feedback on content and software performance, as well as the overall usability. Beta users are advised that information on this site is provided on an "as is" and "as available" basis. The accuracy, completeness or authenticity of the information on the GRSF catalogue is not guaranteed. It is reserved the right to alter, limit or discontinue any part of this service at its discretion. Under no circumstances shall the GRSF be liable for any loss, damage, liability or expense suffered that is claimed to result from the use of information posted on this site, including without limitation, any fault, error, omission, interruption or delay. The GRSF is an active database, updates and additions will continue after the beta release. For further information, or for using the GRSF unique identifiers as a beta tester please contact FIRMS-Secretariat@fao.org.
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The Canadian Institute for Health Information (CIHI) provides comparable and actionable data and information that are used to accelerate improvements in health care, health system performance and population health across Canada.
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The Better Outcomes Registry & Network (BORN) is Ontario's prescribed perinatal, newborn and child registry with the role of facilitating quality care for families across the province. BORN collects, interprets, shares and rigorously protects high-quality data essential to making Ontario the safest place in the world to have a baby.
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GCRIS Database is a research and performance evaluation information system that enables searching and discovering all research outputs within the Izmir Institute of Technology research ecosystem, associating these outputs with researchers, providing advanced reporting with different metrics, and supporting corporate strategic decisions. Besides, it is an institutional repository at international standards that brings together and organizes all kinds of academic outputs related to research activities and allows sharing with the whole scientific world by providing long-term preservation.
Atmosphere to Electrons (A2e) is a new, multi-year, multi-stakeholder U.S. Department of Energy (DOE) research and development initiative tasked with improving wind plant performance and mitigating risk and uncertainty to achieve substantial reduction in the cost of wind energy production. The A2e strategic vision will enable a new generation of wind plant technology, in which smart wind plants are designed to achieve optimized performance stemming from more complete knowledge of the inflow wind resource and complex flow through the wind plant.
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Being both, a demand as well as a chance of the present age of information technology for cultural preservation and continuation, public databases possess an immense importance for providing a comprehensive access to cultural material as far as their contents and also their clientele of users are concerned. Therefore, an exemplary completely preserved stock of primary sources as the one of the Weimar theatre is no less than an invaluable piece of luck, possibly just due to the manageable local conditions of this small (former courtly) town in the middle of German language area. In this English version, first this rare cultural-historical phenomenon and its sources are described. Furthermore, the data- and metadata-contents within the Weimar theatre- and music-ephemera database are presented. Finally, the principal opportunities of searching this (meta-)data pool are explained, where presumed to be necessary supported by screenshot images from the internet platform.
WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.
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The MOSES Data Discovery Portal is the central component of the MOSES data management infrastructure. It holds the metadata of MOSES campaigns, sensors and data and enables high-performance data searches. In addition, it provides access to the decentral data repositories and infrastructures of the participating Helmholtz centers where MOSES data is stored.
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OpARA (Open Access Repository and Archive) is the repository for digital research data of the TU Dresden (TUD) and the TU Bergakademie Freiberg (TUBAF). It offers researchers the possibility of archiving their digital research data and optionally making it accessible to third parties under an Open Access license.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.
HydroShare is a system operated by The Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) that enables users to share and publish data and models in a variety of flexible formats, and to make this information available in a citable, shareable and discoverable manner. HydroShare includes a repository for data and models, and tools (web apps) that can act on content in HydroShare providing users with a gateway to high performance computing and computing in the cloud. With HydroShare you can: share data and models with colleagues; manage access to shared content; share, access, visualize, and manipulate a broad set of hydrologic data types and models; publish data and models and obtain a citable digital object identifier (DOI); aggregate resources into collections; discover and access data and models published by others; use the web services application programming interface (API) to programmatically access resources; and use integrated web applications to visualize, analyze and run models with data in HydroShare.
CSDMS is a virtual home for a vibrant and growing community of about 1,000 international modeling experts and students who study the dynamic interactions of lithosphere, hydrosphere, cryosphere, and atmosphere at Earth’s surface. Participating in cross-disciplinary groups, members develop integrated software modules that predict the movement of water, sediment, and nutrients across landscapes and into the ocean. We share an open library of models, software, and access to high-performance computing. We also share knowledge that helps create higher-resolution simulations, often involving higher complexity algorithms. Together, we support the discovery, use, and conservation of natural resources; mitigation of natural hazards; geotechnical support of commercial and infrastructure development; environmental stewardship; and terrestrial surveillance for global security.
The Phonogrammarchiv is a multi-disciplinary research sound and video archive, covering holdings from all continents. Since its foundation in 1899 the Phonogrammarchiv has been building up its holdings by cooperating with Austrian scholars and archiving their collected material, or by fieldwork conducted by staff members on special topics exploring new fields of methods and contents. The main tasks comprise the production, annotation, cataloguing and long-term preservation of audio-visual field recordings, making the cultural heritage available for future generations and enabling the dissemination of the recordings as well as technical developments in the field of AV recording and storage. Thus the Phonogrammarchiv adds to infrastructural performance valuable to both the scholarly community and the public at large.
HunCLARIN is a strategic research infrastructure of Hungary’s leading knowledge centres involved in R&D in speech- and language processing. It contains linguistic resources and tools that form the basis of research. The infrastructure has obtained an “SKI” qualification (Strategic Research Infrastructure) in 2010, and has been significantly expanded since. Currently comprising 36 members, the infrastructure includes several general- and specific-purpose text corpora, different language processing tools and analysers, linguistic databases as well as ontologies. RIL HAS was a co-founder of the European CLARIN project, which aims at supporting humanities and social sciences research with the help of language technology and by making digital linguistic resources more easily available. In accordance with these goals HunClarin makes the research infrastructures developed by the respective centres directly accessible for researchers through a common network entry point. A general goal of the infrastructure is to realise the interoperability of the collected research infrastructures and to enable comparing the performance of the respective alternatives and to coordinate different foci in R&D. The coordinator and contact person of the infrastructure is Tamás Váradi, RIL HAS.
NASA Life Sciences Portal is the next generation of the Life Sciences Data Archive for Human, Animal and Plant Research NASA's Human Research Program (HRP) conducts research and develops technologies that allow humans to travel safely and productively in space. The Program uses evidence from data collected on astronauts, as well as other supporting studies. These data are stored in the research data repository, Life Sciences Data Archive (LSDA).
Maddison's work contains the Project Dataset with estimates of GDP per capita for all countries in the world between 1820 and 2010 in a format amenable to analysis in R. The database was last updated in January 2013. The update incorporates much of the latest research in the field, and presents new estimates of economic growth in the world economic between AD 1 and 2010 The Maddison Project database presented builts on Angus Maddison's original dataset. The original estimates are kept intact, and only revised or adjusted when there is more and better information available. Angus Maddison's unaltered final dataset remains available on the Original Maddison Homepage https://www.rug.nl/ggdc/historicaldevelopment/maddison/original-maddison
IoT Lab is a research platform exploring the potential of crowdsourcing and Internet of Things for multidisciplinary research with more end-user interactions. IoT Lab is a European Research project which aims at researching the potential of crowdsourcing to extend IoT testbed infrastructure for multidisciplinary experiments with more end-user interactions. It addresses topics such as: - Crowdsourcing mechanisms and tools; - “Crowdsourcing-driven research”; - Virtualization of crowdsourcing and testbeds; - Ubiquitous Interconnection and Cloudification of testbeds; - Testbed as a Service platform; - Multidisciplinary experiments; - End-user and societal value creation; - Privacy and personal data protection.
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With the KIT Whole-Body Human Motion Database, we aim to provide a simple way of sharing high-quality motion capture recordings of human whole-body motion. In addition, with the Motion Annotation Tool (https://motion-annotation.humanoids.kit.edu/ ), we aim to collect a comprehensive set of whole-body motions along with natural language descriptions of these motions (https://motion-annotation.humanoids.kit.edu/dataset/).
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FlyCircuit is a public database for online archiving, cell type inventory, browsing, searching, analysis and 3D visualization of individual neurons in the Drosophila brain. The FlyCircuit Database currently contains about 30,000 high resolution 3D brain neural images of the drosophila fruit fly brain that are combined into a neural circuitry network that researchers can use as a blueprint to further explore how the brain of a fruit fly processes external sensory signals (i.e. how vision, hearing, and smell are transmitted to the central nerve system).
Using a combination of remote sensing data and ground observations as inputs, CHC scientists have developed rainfall estimation techniques and other resources to support drought monitoring and predict crop performance in parts of the world vulnerable to crop failure. Policymakers within governments and non-governmental organizations rely on CHC decision-support products to make critical resource allocation decisions. The CHC's scientific focus is "geospatial hydroclimatology," with an emphasis on the early detection and forecasting of hydroclimatic hazards related to food-security droughts and floods. Basic research seeks an improved understanding of the climatic processes that govern drought and flood hazards in FEWS NET countries (https://fews.net/). The CHC develops better techniques, algorithms, and modeling applications in order to use remote sensing and other geospatial data for hazards early warning.