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Found 24 result(s)
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CCCma has developed a number of climate models. These are used to study climate change and variability, and to understand the various processes which govern the climate system. They are also used to make quantitative projections of future long-term climate change (given various greenhouse gas and aerosol forcing scenarios), and increasingly to make initialized climate predictions on time scales ranging from seasons to decades. A brief description of these models and their corresponding references can be found: https://www.canada.ca/en/environment-climate-change/services/climate-change/science-research-data/modeling-projections-analysis/centre-modelling-analysis/models.html
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
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Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. Kadi4Mat is the Karlsruhe Data Infrastructure for Materials Science, an open source software for managing research data. It is being developed as part of several research projects at the Institute for Applied Materials - Microstructure Modelling and Simulation (IAM-MMS) of the Karlsruhe Institute of Technology (KIT). The goal of this project is to combine the ability to manage and exchange data, the repository , with the possibility to analyze, visualize and transform said data, the electronic lab notebook (ELN). Kadi4Mat supports a close cooperation between experimenters, theorists and simulators, especially in materials science, to enable the acquisition of new knowledge and the development of novel materials. This is made possible by employing a modular and generic architecture, which allows to cover the specific needs of different scientists, each utilizing unique workflows. At the same time, this opens up the possibility of covering other research disciplines as well.
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HYdrological cycle in the Mediterranean EXperiemnt. Considering the science and societal issues motivating HyMeX, the programme aims to : improve our understanding of the water cycle, with emphasis on extreme events, by monitoring and modelling the Mediterranean atmosphere-land-ocean coupled system, its variability from the event to the seasonal and interannual scales, and its characteristics over one decade (2010-2020) in the context of global change, assess the social and economic vulnerability to extreme events and adaptation capacity.The multidisciplinary research and the database developed within HyMeX should contribute to: improve observational and modelling systems, especially for coupled systems, better predict extreme events, simulate the long-term water-cycle more accurately, provide guidelines for adaptation measures, especially in the context of global change.
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The NOMAD Repository and Archive stands for open access of scientific materials data. It enables the confirmatory analysis of materials data, their reuse, and repurposing. All data is available in their raw format as produced by the underlying code (Repository) and in a common, machine-processable, and well-defined data format (Archive).
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The UniSA Data Access Portal showcases a range of Open Access research collections and datasets developed or collected by the University of South Australia. The UniSA Data Access Portal also highlights research projects and publications related to the available collections and datasets, and facilitates a variety of searches by researcher, organisation, discipline and keyword. Research collections and datasets available in Open Access can be freely downloaded and used to support your research in line with the terms of the licence under which they are made available.
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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.
The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for international co-operation to solve transboundary air pollution problems.
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical state, variability and dynamics of the ocean and marine ecosystems for the global ocean and the European regional seas. The observations and forecasts produced by the service support all marine applications, including: Marine safety; Marine resources; Coastal and marine environment; Weather, seasonal forecasting and climate. For instance, the provision of data on currents, winds and sea ice help to improve ship routing services, offshore operations or search and rescue operations, thus contributing to marine safety. The service also contributes to the protection and the sustainable management of living marine resources in particular for aquaculture, sustainable fisheries management or regional fishery organisations decision-making process. Physical and marine biogeochemical components are useful for water quality monitoring and pollution control. Sea level rise is a key indicator of climate change and helps to assess coastal erosion. Sea surface temperature elevation has direct consequences on marine ecosystems and appearance of tropical cyclones. As a result of this, the service supports a wide range of coastal and marine environment applications. Many of the data delivered by the service (e.g. temperature, salinity, sea level, currents, wind and sea ice) also play a crucial role in the domain of weather, climate and seasonal forecasting.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.
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The CRC1211DB is the project-database of the Collaborative Research Centre 1211 "Earth -Evolution at the dry limit" (CRC1211,https://sfb1211.uni-koeln.de/) funded by the German Research Foundation (DFG, German Research Foundation – Projektnummer 268236062). The project-database is a new implementation of the TR32DB and online since 2016. It 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, biology, geography, geology, meteorology and 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.
The projects include airborne, ground-based and ocean measurements, social science surveys, satellite data use, modelling studies and value-added product development. Therefore, the BAOBAB data portal enables to access a great amount and a large variety of data: - 250 local observation datasets, that have been collected by operational networks since 1850, long term monitoring research networks and intensive scientific campaigns; - 1350 outputs of a socio-economics questionnaire; - 60 operational satellite products and several research products; - 10 output sets of meteorological and ocean operational models and 15 of research simulations. Data documentation complies with metadata international standards, and data are delivered into standard formats. The data request interface takes full advantage of the database relational structure and enables users to elaborate multicriteria requests (period, area, property…).
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From April 2020 to March 2023, the Covid-19 Immunity Task Force (CITF) supported 120 studies to generate knowledge about immunity to SARS-CoV-2. The subjects addressed by these studies include the extent of SARS-CoV-2 infection in Canada, the nature of immunity, vaccine effectiveness and safety, and the need for booster shots among different communities and priority populations in Canada. The CITF Databank was developed to further enhance the impact of CITF funded studies by allowing additional research using the data collected from CITF-supported studies. The CITF Databank centralizes and harmonizes individual-level data from CITF-funded studies that have met all ethical requirements to deposit data in the CITF Databank and have completed a data sharing agreement. The CITF Databank is an internationally unique resource for sharing epidemiological and laboratory data from studies about SARS-CoV-2 immunity in different populations. The types of research that are possible with data from the CITF Databank include observational epidemiological studies, mathematical modelling research, and comparative evaluation of surveillance and laboratory methods.
Climate4impact: a dedicated interface to ESGF for the climate impact community The portal Climate4impact, part of the ENES Data Infrastructure, provides access to data and quick looks of global and regional climate models and downscaled higher resolution climate data. The portal provides data transformation tooling and mapping & plotting capabilities, guidance, documentation, FAQ and examples. The Climate4Impact portal will be further developed during the IS-ENES3 project (2019-2023)and moved to a different environment. Meanwhile the portal at https://climate4impact.eu will remain available, but no new information or processing options will be included. When the new portal will become available this will be announced on https://is.enes.org/.
THEREDA (Thermodynamic Reference Database) is a joint project dedicated to the creation of a comprehensive, internally consistent thermodynamic reference database, to be used with suitable codes for the geochemical modeling of aqueous electrolyte solutions up to high concentrations.
When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.
Under the World Climate Research Programme (WCRP) the Working Group on Coupled Modelling (WGCM) established the Coupled Model Intercomparison Project (CMIP) as a standard experimental protocol for studying the output of coupled atmosphere-ocean general circulation models (AOGCMs). CMIP provides a community-based infrastructure in support of climate model diagnosis, validation, intercomparison, documentation and data access. This framework enables a diverse community of scientists to analyze GCMs in a systematic fashion, a process which serves to facilitate model improvement. Virtually the entire international climate modeling community has participated in this project since its inception in 1995. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) archives much of the CMIP data and provides other support for CMIP. We are now beginning the process towards the IPCC Fifth Assessment Report and with it the CMIP5 intercomparison activity. The CMIP5 (CMIP Phase 5) experiment design has been finalized with the following suites of experiments: I Decadal Hindcasts and Predictions simulations, II "long-term" simulations, III "atmosphere-only" (prescribed SST) simulations for especially computationally-demanding models. The new ESGF peer-to-peer (P2P) enterprise system (http://pcmdi9.llnl.gov) is now the official site for CMIP5 model output. The old gateway (http://pcmdi3.llnl.gov) is deprecated and now shut down permanently.
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>>>!!!<<< The repository is no longer available. >>>!!!<<< C3-Grid is an ALREADY FINISHED project within D-Grid, the initiative to promote a grid-based e-Science framework in Germany. The goal of C3-Grid is to support the workflow of Earth system researchers. A grid infrastructure will be implemented that allows efficient distributed data processing and inter-institutional data exchange. Aim of the effort was to develop an infrastructure for uniform access to heterogeneous data and distributed data processing. The work was structured in two projects funded by the Federal Ministry of Education and Research. The first project was part of the D-Grid initiative and explored the potential of grid technology for climate research and developed a prototype infrastructure. Details about the C3Grid architecture are described in “Earth System Modelling – Volume 6”. In the second phase "C3Grid - INAD: Towards an Infrastructure for General Access to Climate Data" this infrastructure was improved especially with respect to interoperability to Earth System Grid Federation (ESGF). Further the portfolio of available diagnostic workflows was expanded. These workflows can be re-used now in adjacent infrastructures MiKlip Evaluation Tool (http://www.fona-miklip.de/en/index.php) and as Web Processes within the Birdhouse Framework (http://bird-house.github.io/). The Birdhouse Framework is now funded as part of the European Copernicus Climate Change Service (https://climate.copernicus.eu/) managed by ECMWF and will be extended to provide scalable processing services for ESGF hosted data at DKRZ as well as IPSL and BADC.
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.