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Found 14 result(s)
Chempound is a new generation repository architecture based on RDF, semantic dictionaries and linked data. It has been developed to hold any type of chemical object expressible in CML and is exemplified by crystallographic experiments and computational chemistry calculations. In both examples, the repository can hold >50k entries which can be searched by SPARQL endpoints and pre-indexing of key fields. The Chempound architecture is general and adaptable to other fields of data-rich science. The Chempound software is hosted at http://bitbucket.org/chempound and is available under the Apache License, Version 2.0
The PeptideAtlas validates expressed proteins to provide eukaryotic genome data. Peptide Atlas provides data to advance biological discoveries in humans. The PeptideAtlas accepts proteomic data from high-throughput processes and encourages data submission.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
MassBank of North America (MoNA) is a metadata-centric, auto-curating repository designed for efficient storage and querying of mass spectral records. It intends to serve as a the framework for a centralized, collaborative database of metabolite mass spectra, metadata and associated compounds. MoNA currently contains over 200,000 mass spectral records from experimental and in-silico libraries as well as from user contributions.
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.
The Integrated Resource for Reproducibility in Macromolecular Crystallography includes a repository system and website designed to make the raw data of protein crystallography more widely available. Our focus is on identifying, cataloging and providing the metadata related to datasets, which could be used to reprocess the original diffraction data. The intent behind this project is to make the resulting three dimensional structures more reproducible and easier to modify and improve as processing methods advance.
---<<< 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.
The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is a team of researchers, data specialists and computer system developers who are supporting the development of a data management system to store scientific data generated by Gulf of Mexico researchers. The Master Research Agreement between BP and the Gulf of Mexico Alliance that established the Gulf of Mexico Research Initiative (GoMRI) included provisions that all data collected or generated through the agreement must be made available to the public. The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is the vehicle through which GoMRI is fulfilling this requirement. The mission of GRIIDC is to ensure a data and information legacy that promotes continual scientific discovery and public awareness of the Gulf of Mexico Ecosystem.
The Magnetics Information Consortium (MagIC) improves research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock magnetic, geomagnetic, archeomagnetic (archaeomagnetic) and paleomagnetic (palaeomagnetic) data. Different parts of the website allow users access to archive, search, visualize, and download these data. MagIC supports the international rock magnetism, geomagnetism, archeomagnetism (archaeomagnetism), and paleomagnetism (palaeomagnetism) research and endeavors to bring data out of private archives, making them accessible to all and (re-)useable for new, creative, collaborative scientific and educational activities. The data in MagIC is used for many types of studies including tectonic plate reconstructions, geomagnetic field models, paleomagnetic field reversal studies, magnetohydrodynamical studies of the Earth's core, magnetostratigraphy, and archeology. MagIC is a domain-specific data repository and directed by PIs who are both producers and consumers of rock, geo, and paleomagnetic data. Funded by NSF since 2003, MagIC forms a major part of https://earthref.org which integrates four independent cyber-initiatives rooted in various parts of the Earth, Ocean and Life sciences and education.