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Found 168 result(s)
Remote Sensing Systems is a world leader in processing and analyzing microwave data from satellite microwave sensors. We specialize in algorithm development, instrument calibration, ocean product development, and product validation. We have worked with more than 30 satellite microwave radiometer, sounder, and scatterometer instruments over the past 40 years. Currently, we operationally produce satellite retrievals for SSMIS, AMSR2, WindSat, and ASCAT. The geophysical retrievals obtained from these sensors are made available in near-real-time (NRT) to the global scientific community and general public via FTP and this web site.
GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. With the collaborative features of GitHub.com, our desktop and mobile apps, and GitHub Enterprise, it has never been easier for individuals and teams to write better code, faster. Originally founded by Tom Preston-Werner, Chris Wanstrath, and PJ Hyett to simplify sharing code, GitHub has grown into the largest code host in the world.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> The Plant Organelles Database Version 3 (PODB3) is a specialized database project to promote a comprehensive understanding of organelle dynamics, including organelle function, biogenesis, differentiation, movement, and interactions with other organelles. This database consists of 6 individual parts, 'The Electron Micrograph Database', 'The Perceptive Organelles Database', 'The Organelles Movie Database', 'The Organellome Database', 'The Functional Analysis Database', and 'External Links to other databases and Web pages'. All the data and protocols in these databases are populated by direct submission of experimentally determined data from plant researchers.
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 National Population Health Data Center (NPHDC) is one of the 20 national science data center approved by the Ministry of Science and Technology and the Ministry of Finance. The Population Health Data Archive (PHDA) is developed by NPHDC relying on the Institute of Medical Information, Chinese Academy of Medical Sciences. PHDA mainly receives scientific data from science and technology projects supported by the national budget, and also collects data from other multiple sources such as medical and health institutions, research institutions and social individuals, which is oriented to the national big data strategy and the healthy China strategy. The data resources cover basic medicine, clinical medicine, public health, traditional Chinese medicine and pharmacy, pharmacy, population and reproduction. PHDA supports data collection, archiving, processing, storage, curation, verification, certification and release in the field of population health. Provide multiple types of data sharing and application services for different hierarchy users and help them find, access, interoperate and reuse the data in a safe and controlled environment. PHDA provides important support for promoting the open sharing of scientific data of population health and domestic and foreign cooperation.
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.
York Digital Library (YODL) is a University-wide Digital Library service for multimedia resources used in or created through teaching, research and study at the University of York. YODL complements the University's research publications, held in White Rose Research Online and PURE, and the digital teaching materials in the University's Yorkshare Virtual Learning Environment. YODL contains a range of collections, including images, past exam papers, masters dissertations and audio. Some of these are available only to members of the University of York, whilst other material is available to the public. YODL is expanding with more content being added all the time
Tthe Lipidomics Gateway - a free, comprehensive website for researchers interested in lipid biology, provided by the LIPID MAPS (Lipid Metabolites and Pathways Strategy) Consortium. The LIPID MAPS Lipidomics Gateway provides a rich collection of information and resources to help you stay abreast of the latest developments in this rapidly expanding field. LIPID Metabolites And Pathways Strategy (LIPID MAPS®) is a multi-institutional effort created in 2003 to identify and quantitate, using a systems biology approach and sophisticated mass spectrometers, all of the major — and many minor — lipid species in mammalian cells, as well as to quantitate the changes in these species in response to perturbation. The ultimate goal of our research is to better understand lipid metabolism and the active role lipids play in diabetes, stroke, cancer, arthritis, Alzheimer's and other lipid-based diseases in order to facilitate development of more effective treatments. Since our inception, we have made great strides toward defining the "lipidome" (an inventory of the thousands of individual lipid molecular species) in the mouse macrophage. We have also worked to make lipid analysis easier and more accessible for the broader scientific community and to advance a robust research infrastructure for the international research community. We share new lipidomics findings and methods, hold annual meetings open to all interested investigators, and are exploring joint efforts to extend the use of these powerful new methods to new applications
The Cornell Center for Social Sciences (CCSS) houses an extensive collection of research data files in the social sciences with particular emphasis on data that matches the interests of Cornell University researchers. CCSS intentionally uses a broad definition of social sciences in recognition of the interdisciplinary nature of Cornell research. CCSS collects and maintains digital research data files in the social sciences, with a current emphasis on Cornell-based social science research, Results Reproduction packages, and potentially at-risk datasets. Our archive historically has focused on a broad range of social science data, including data on demography, economics and labor, political and social behavior, family life, and health. You can search our holdings or browse studies by subject area.
Data products developed and distributed by the National Institute of Standards and Technology span multiple disciplines of research and are widely used in research and development programs by industry and academia. NIST's publicly available data sets showcase its committment to providing accurate, well-curated measurements of physical properties, exemplified by the Standard Reference Data program, as well as its committment to advancing basic research. In accordance with U.S. Government Open Data Policy and the NIST Plan for providing public access to the results of federally funded research data, NIST maintains a publicly accessible listing of available data, the NIST Public Dataset List (json). Additionally, these data are assigned a Digital Object Identifier (DOI) to increase the discovery and access to research output; these DOIs are registered with DataCite and provide globally unique persistent identifiers. The NIST Science Data Portal provides a user-friendly discovery and exploration tool for publically available datasets at NIST. This portal is designed and developed with data.gov Project Open Data standards and principles. The portal software is hosted in the usnistgov github repository.
<<<!!!<<< Stated 2019-10-30: Dash is no longer available. Researchers are advised to store their research data at Dryad https://www.re3data.org/repository/r3d100000044 >>>!!!>>> Dash is an open data publication platform for upload, access, and re-use of research data. Submissions to Dash may be from researchers at participating UC campuses, researchers in earth science and ecology (DataONE), and researchers submitting to the UC Press journals Elementa and Collabra. Self-service depositing of research data through Dash fulfills publisher, funder, and data management plan requirements regarding data sharing and preservation. When researchers publish their datasets through Dash, their datasets are issued a DOI (DataCite) to optimize citability, and are publicly available for download and re-use under a CC BY 4.0 or CC-0 license. Deposited data are preserved in Merritt, California Digital Library’s preservation repository.
California Digital Library (CDL) seeks to be a catalyst for deeply collaborative solutions providing a rich, intuitive and seamless environment for publishing, sharing and preserving our scholars’ increasingly diverse outputs, as well as for acquiring and accessing information critical to the University of California’s scholarly enterprise. University of California Curation Center (UC3) is the digital curation program within CDL. The mission of UC3 is to provide transformative preservation, curation, and research data management systems, services, and initiatives that sustain and promote open scholarship.
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies
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 BioCyc database collection of Pathway/Genome Databases (PGDBs) provides a reference on the genomes and metabolic pathways of thousands of sequenced organisms. BioCyc PGDBs are generated by software that predict the metabolic pathways of completely sequenced organisms, predict which genes code for missing enzymes in metabolic pathways, and predict operons. BioCyc also integrates information from other bioinformatics databases, such as protein feature and Gene Ontology information from UniProt. The BioCyc website provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. From 2016 on, access to the EcoCyc and MetaCyc databases will remain free. Subscriptions to the other 7,600 BioCyc databases will be available to institutions (e.g., libraries), and to individuals. Access to licensed databases via: https://biocyc.org/Product-summary.shtml.
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<<<!!!<< With the implementation of GlyTouCan (https://glytoucan.org/) the mission of GlycomeDB comes to an end. >>>!!!>>> With the new database, GlycomeDB, it is possible to get an overview of all carbohydrate structures in the different databases and to crosslink common structures in the different databases. Scientists are now able to search for a particular structure in the meta database and get information about the occurrence of this structure in the five carbohydrate structure databases.