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Found 14 result(s)
---<<< This repository is no longer available. This record is out-dated >>>--- The ONS challenge contains open solubility data, experiments with raw data from different scientists and institutions. It is part of the The Open Notebook Science wiki community, ideally suited for community-wide collaborative research projects involving mathematical modeling and computer simulation work, as it allows researchers to document model development in a step-by-step fashion, then link model prediction to experiments that test the model, and in turn, use feeback from experiments to evolve the model. By making our laboratory notebooks public, the evolutionary process of a model can be followed in its totality by the interested reader. Researchers from laboratories around the world can now follow the progress of our research day-to-day, borrow models at various stages of development, comment or advice on model developments, discuss experiments, ask questions, provide feedback, or otherwise contribute to the progress of science in any manner possible.
Surrey Research Insight (SRI) is an open access resource that hosts, preserves and disseminates the full text of scholarly papers produced by members of the University of Surrey. Its main purpose is to help Surrey authors make their research more widely known; their ideas and findings readily accessible; and their papers more frequently read and cited. Surrey Research Insight (formerly Surrey Scholarship Online) was developed in line with the Open Access Initiative, promoting free access to scholarship for the benefit of authors and scholars. It is one of many open access repositories around the world that operate on agreed standards to ensure wide and timely dissemination of research.
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.
The National Deep Submergence Facility (NDSF) operates the Human Occupied Vehicle (HOV) Alvin, the Remote Operated Vehicle (ROV) Jason 2, and the Autonomous Underwater Vehicle (AUV) Sentry. Data acquired with these platforms is provided both to the science party on each expedition, and to the Woods Hole Oceanographic Institution (WHOI) Data Library.
State of the Salmon provides data on abundance, diversity, and ecosystem health of wild salmon populations specific to the Pacific Ocean, North Western North America, and Asia. Data downloads are available using two geographic frameworks: Salmon Ecoregions or Hydro 1K.
The Portal aims to serve as a unique access point to timely, comprehensive migration statistics and reliable information about migration data globally. The site is designed to help policy makers, national statistics officers, journalists and the general public interested in the field of migration to navigate the increasingly complex landscape of international migration data, currently scattered across different organisations and agencies. Especially in critical times, such as those faced today, it is essential to ensure that responses to migration are based on sound facts and accurate analysis. By making the evidence about migration issues accessible and easy to understand, the Portal aims to contribute to a more informed public debate. The Portal was launched in December 2017 and is managed and developed by IOM’s Global Migration Data Analysis Centre (GMDAC), with the guidance of its Advisory Board, and was supported in its conception by the Economist Intelligence Unit (EIU). The Portal is supported financially by the Governments of Germany, the United States of America and the UK Department for International Development (DFID).
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
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The Fish Database of Taiwan is a complex of research data for about 25 years to the Lab of Fish Ecology and Evolution, which is situated in Biodiversity Research Center of Academia Sinica.
The U.S. launched the Joint Global Ocean Flux Study (JGOFS) in the late 1980s to study the ocean carbon cycle. An ambitious goal was set to understand the controls on the concentrations and fluxes of carbon and associated nutrients in the ocean. A new field of ocean biogeochemistry emerged with an emphasis on quality measurements of carbon system parameters and interdisciplinary field studies of the biological, chemical and physical process which control the ocean carbon cycle. As we studied ocean biogeochemistry, we learned that our simple views of carbon uptake and transport were severely limited, and a new "wave" of ocean science was born. U.S. JGOFS has been supported primarily by the U.S. National Science Foundation in collaboration with the National Oceanic and Atmospheric Administration, the National Aeronautics and Space Administration, the Department of Energy and the Office of Naval Research. U.S. JGOFS, ended in 2005 with the conclusion of the Synthesis and Modeling Project (SMP).
The main goal of the ECCAD project is to provide scientific and policy users with datasets of surface emissions of atmospheric compounds, and ancillary data, i.e. data required to estimate or quantify surface emissions. The supply of ancillary data - such as maps of population density, maps of fires spots, burnt areas, land cover - could help improve and encourage the development of new emissions datasets. ECCAD offers: Access to global and regional emission inventories and ancillary data, in a standardized format Quick visualization of emission and ancillary data Rationalization of the use of input data in algorithms or emission models Analysis and comparison of emissions datasets and ancillary data Tools for the evaluation of emissions and ancillary data ECCAD is a dynamical and interactive database, providing the most up to date datasets including data used within ongoing projects. Users are welcome to add their own datasets, or have their regional masks included in order to use ECCAD tools.
The COVID-19 pandemic has affected every country in the world. It is well documented that those most susceptible to the worst outcomes of COVID-19 are the immunocompromised and those with underlying comorbidities. Therefore, patients requiring treatment for COVID-19 will also be on additional medication, posing a risk for drug-drug interactions (DDIs). In order to address this, the Liverpool Drug Interactions website team developed this freely available drug interactions resource to provide information on the likelihood of interactions between the experimental agents used for the treatment of COVID-19 and commonly prescribed co-medications.
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The Global Proteome Machine (GPM) is a protein identification database. This data repository allows users to post and compare results. GPM's data is provided by contributors like The Informatics Factory, University of Michigan, and Pacific Northwestern National Laboratories. The GPM searchable databases are: GPMDB, pSYT, SNAP, MRM, PEPTIDE and HOT.
The Open Exoplanet Catalogue is a catalogue of all discovered extra-solar planets. It is a new kind of astronomical database. It is decentralized and completely open. We welcome contributions and corrections from both professional astronomers and the general public.