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Found 21 result(s)
The FishNet network is a collaborative effort among fish collections around the world to share and distribute data on specimen holdings. There is an open invitation for any institution with a fish collection to join.
We are a leading international centre for genomics and bioinformatics research. Our mandate is to advance knowledge about cancer and other diseases, to improve human health through disease prevention, diagnosis and therapeutic approaches, and to realize the social and economic benefits of genomics research.
The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).
IntAct provides a freely available, open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions and are freely available.
The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc).
EarthWorks is a discovery tool for geospatial (a.k.a. GIS) data. It allows users to search and browse the GIS collections owned by Stanford University Libraries, as well as data collections from many other institutions. Data can be searched spatially, by manipulating a map; by keyword search; by selecting search limiting facets (e.g., limit to a given format type); or by combining these options.
TERN provides open data, research and management tools, data infrastructure and site-based research equipment. The open access ecosystem data is provided by TERN Data Discovery Portal , see https://www.re3data.org/repository/r3d100012013
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.
The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is a publicly accessible earth science data repository created to curate, publicly serve (publish), and archive digital data and information from biological, chemical and biogeochemical research conducted in coastal, marine, great lakes and laboratory environments. The BCO-DMO repository works closely with investigators funded through the NSF OCE Division’s Biological and Chemical Sections and the Division of Polar Programs Antarctic Organisms & Ecosystems. The office provides services that span the full data life cycle, from data management planning support and DOI creation, to archive with appropriate national facilities.
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.
NKN is now Research Computing and Data Services (RCDS)! We provide data management support for UI researchers and their regional, national, and international collaborators. This support keeps researchers at the cutting-edge of science and increases our institution's competitiveness for external research grants. Quality data and metadata developed in research projects and curated by RCDS (formerly NKN) is a valuable, long-term asset upon which to develop and build new research and science.
Harmonized, indexed, searchable large-scale human FG data collection with extensive metadata. Provides scalable, unified way to easily access massive functional genomics (FG) and annotation data collections curated from large-scale genomic studies. Direct integration (API) with custom / high-throughput genetic and genomic analysis workflows.
Open Context is a free, open access resource for the electronic publication of primary field research from archaeology and related disciplines. It emerged as a means for scholars and students to easily find and reuse content created by others, which are key to advancing research and education. Open Context's technologies focus on ease of use, open licensing frameworks, informal data integration and, most importantly, data portability.Open Context currently publishes 132 projects.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
The Registry of Open Data on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge to their users. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
Weed Images is a project of the University of Georgia’s Center for Invasive Species and Ecosystem Health and one of the four major parts of BugwoodImages. The Focus is on damages of weed. It provides an easily accessible archive of high quality images for use in educational applications. In most cases, the images found in this system were taken by and loaned to us by photographers other than ourselves. Most are in the realm of public sector images. The photographs are in this system to be used.
The Marine Geoscience Data System (MGDS) is a trusted data repository that provides free public access to a curated collection of marine geophysical data products and complementary data related to understanding the formation and evolution of the seafloor and sub-seafloor. Developed and operated by domain scientists and technical specialists with deep knowledge about the creation, analysis and scientific interpretation of marine geoscience data, the system makes available a digital library of data files described by a rich curated metadata catalog. MGDS provides tools and services for the discovery and download of data collected throughout the global oceans. Primary data types are geophysical field data including active source seismic data, potential field, bathymetry, sidescan sonar, near-bottom imagery, other seafloor senor data as well as a diverse array of processed data and interpreted data products (e.g. seismic interpretations, microseismicity catalogs, geologic maps and interpretations, photomosaics and visualizations). Our data resources support scientists working broadly on solid earth science problems ranging from mid-ocean ridge, subduction zone and hotspot processes, to geohazards, continental margin evolution, sediment transport at glaciated and unglaciated margins.
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.
The Ensembl project produces genome databases for vertebrates and other eukaryotic species. Ensembl is a joint project between the European Bioinformatics Institute (EBI) and the Wellcome Trust Sanger Institute (WTSI) to develop a software system that produces and maintains automatic annotation on selected genomes.The Ensembl project was started in 1999, some years before the draft human genome was completed. Even at that early stage it was clear that manual annotation of 3 billion base pairs of sequence would not be able to offer researchers timely access to the latest data. The goal of Ensembl was therefore to automatically annotate the genome, integrate this annotation with other available biological data and make all this publicly available via the web. Since the website's launch in July 2000, many more genomes have been added to Ensembl and the range of available data has also expanded to include comparative genomics, variation and regulatory data. Ensembl is a joint project between European Bioinformatics Institute (EBI), an outstation of the European Molecular Biology Laboratory (EMBL), and the Wellcome Trust Sanger Institute (WTSI). Both institutes are located on the Wellcome Trust Genome Campus in Hinxton, south of the city of Cambridge, United Kingdom.