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Found 10 result(s)
OBIS strives to document the ocean's diversity, distribution and abundance of life. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
The Allen Brain Atlas provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate
The OpenMadrigal project seeks to develop and support an on-line database for geospace data. The project has been led by MIT Haystack Observatory since 1980, but now has active support from Jicamarca Observatory and other community members. Madrigal is a robust, World Wide Web based system capable of managing and serving archival and real-time data, in a variety of formats, from a wide range of ground-based instruments. Madrigal is installed at a number of sites around the world. Data at each Madrigal site is locally controlled and can be updated at any time, but shared metadata between Madrigal sites allow searching of all Madrigal sites at once from any Madrigal site. Data is local; metadata is shared.
>>>!!!<<< This site is going away on April 1, 2021. General access to the site has been disabled and community users will see an error upon login. >>>!!!<<< Socrata’s cloud-based solution allows government organizations to put their data online, make data-driven decisions, operate more efficiently, and share insights with citizens.
LinkedEarth is an EarthCube-funded project aiming to better organize and share Earth Science data, especially paleoclimate data. LinkedEarth facilitates the work of scientists by empowering them to curate their own data and to build new tools centered around those.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
<<<!!!<<< All user content from this site has been deleted. Visit SeedMeLab (https://seedmelab.org/) project as a new option for data hosting. >>>!!!>>> SeedMe is a result of a decade of onerous experience in preparing and sharing visualization results from supercomputing simulations with many researchers at different geographic locations using different operating systems. It’s been a labor–intensive process, unsupported by useful tools and procedures for sharing information. SeedMe provides a secure and easy-to-use functionality for efficiently and conveniently sharing results that aims to create transformative impact across many scientific domains.
The LINZ Data Service provides free online access to New Zealand’s most up-to-date land and seabed data. The data can be searched, browsed and downloaded. The LINZ web services can be also integrated into other applications.
Data.gov increases the ability of the public to easily find, download, and use datasets that are generated and held by the Federal Government. Data.gov provides descriptions of the Federal datasets (metadata), information about how to access the datasets, and tools that leverage government datasets
The SuiteSparse Matrix Collection is a large and actively growing set of sparse matrices that arise in real applications. The Collection is widely used by the numerical linear algebra community for the development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments. Its matrices cover a wide spectrum of domains, include those arising from problems with underlying 2D or 3D geometry (as structural engineering, computational fluid dynamics, model reduction, electromagnetics, semiconductor devices, thermodynamics, materials, acoustics, computer graphics/vision, robotics/kinematics, and other discretizations) and those that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs.