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Found 107 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.
>>>!!!<<< The repository is no longer available. >>>!!!<<< 2021-06-17; VentDB data collections now housed in the EarthChem Library VentDB is an effort funded by the US National Science Foundation to build and operate a data management system for hydrothermal spring geochemistry that will host and serve the full range of compositional data acquired on seafloor hydrothermal vents from all tectonic settings. VentDB supports the preservation and dissemination of analytical data on hydrothermal springs and plumes. VentDB complements existing geochemical data collections such as SedDB and PetDB. VentDB can accommodate published historical data as well as legacy and new data that investigators contribute. Content of VentDB is static and will not be updated until further notice.
Scholars' Bank is the open access repository for the intellectual work of faculty, students and staff at the University of Oregon and partner institution collections.
Country
The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
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The NWT Discovery Portal is the most comprehensive online source for environmental monitoring knowledge in the Northwest Territories. It is administered by the NWT Cumulative Impact Monitoring Program. The Portal is a search tool that allows users to access data, metadata and reports. It is also a share tool that allows users to contribute by uploading research and monitoring information.
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library. It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. SNAP is also available through the NodeXL which is a graphical front-end that integrates network analysis into Microsoft Office and Excel. The SNAP library is being actively developed since 2004 and is organically growing as a result of our research pursuits in analysis of large social and information networks. Largest network we analyzed so far using the library was the Microsoft Instant Messenger network from 2006 with 240 million nodes and 1.3 billion edges. The datasets available on the website were mostly collected (scraped) for the purposes of our research. The website was launched in July 2009.
nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.
OHSU Digital Commons is a repository for the scholarly and creative work of Oregon Health & Science University. Developed by the OHSU Library, Digital Commons provides the university community with a platform for publishing and accessing content produced by students, faculty, and staff. OHSU Digital Commons documents the history and growth of the university, as well as current progress in education, research, and health care.
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The majority of the CIS research activity focuses on carrying out public opinion surveys. These surveys include electoral studies, its monthly public opinion barometers, monographic studies on different aspects of Spanish society and the surveys resulting from CIS involvement in international projects. All the surveys the CIS takes are deposited in its Data Bank, and they are available to the public once the quality control, verification, anonymisation, codification and information uploading tasks have been concluded. In addition to its surveys, the CIS also collects information about Spanish society through qualitative research studies: Fundamentally, discussion groups and in-depth interviews.
<<<!!!<<< The repository is no longer available. further information and data see: Oxford University Research Archive: https://www.re3data.org/repository/r3d100011230 >>>!!!>>>
All ADNI data are shared without embargo through the LONI Image and Data Archive (IDA), a secure research data repository. Interested scientists may obtain access to ADNI imaging, clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies. "The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls. "
The Seamount Catalog is a digital archive for bathymetric seamount maps from all the oceans that can be viewed and downloaded in various formats. This catalog contains morphological data, sample information, related grid and multibeam data files, as well as user-contributed files that all can be downloaded.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> C3-Grid is an ALREADY FINISHED project within D-Grid, the initiative to promote a grid-based e-Science framework in Germany. The goal of C3-Grid is to support the workflow of Earth system researchers. A grid infrastructure will be implemented that allows efficient distributed data processing and inter-institutional data exchange. Aim of the effort was to develop an infrastructure for uniform access to heterogeneous data and distributed data processing. The work was structured in two projects funded by the Federal Ministry of Education and Research. The first project was part of the D-Grid initiative and explored the potential of grid technology for climate research and developed a prototype infrastructure. Details about the C3Grid architecture are described in “Earth System Modelling – Volume 6”. In the second phase "C3Grid - INAD: Towards an Infrastructure for General Access to Climate Data" this infrastructure was improved especially with respect to interoperability to Earth System Grid Federation (ESGF). Further the portfolio of available diagnostic workflows was expanded. These workflows can be re-used now in adjacent infrastructures MiKlip Evaluation Tool (http://www.fona-miklip.de/en/index.php) and as Web Processes within the Birdhouse Framework (http://bird-house.github.io/). The Birdhouse Framework is now funded as part of the European Copernicus Climate Change Service (https://climate.copernicus.eu/) managed by ECMWF and will be extended to provide scalable processing services for ESGF hosted data at DKRZ as well as IPSL and BADC.
>>>!!!<<< On June 1, 2020, the Academic Seismic Portal repositories at UTIG were merged into a single collection hosted at Lamont-Doherty Earth Observatory. Content here was removed July 1, 2020. Visit the Academic Seismic Portal @LDEO! https://www.marine-geo.org/collections/#!/collection/Seismic#summary (https://www.re3data.org/repository/r3d100010644) >>>!!!<<<
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
MycoCosm, the DOE JGI’s web-based fungal genomics resource, which integrates fungal genomics data and analytical tools for fungal biologists. It provides navigation through sequenced genomes, genome analysis in context of comparative genomics and genome-centric view. MycoCosm promotes user community participation in data submission, annotation and analysis.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
RC content presented through one of our portals is peer reviewed, while the remaining expositions and other information are quality controlled by the individual author(s) themselves. As a result, the RC is highly inclusive. The open source status of the RC is essential to its nature and serves its function as a connective and transitional layer between academic discourse and artistic practice, thereby constituting a discursive field for artistic research.
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The Genome Warehouse (GWH) is a public repository housing genome-scale data for a wide range of species and delivering a series of web services for genome data submission, storage, release and sharing.
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The ZBW Journal Data Archive is a service for editors of journals in economics and management. The Journal Data Archive offers the possibility for journal authors of papers that contain empirical work, simulations or experimental work to store the data, programs, and other details of computations, to make these files publicly available and to support confirmability and replicability of their published research papers.
Government of Yukon open data provides an easy way to find, access and reuse the government's public datasets. This service brings all of the government's data together in one searchable website. Our datasets are created and managed by different government departments. We cannot guarantee the quality or timeliness of all data. If you have any feedback you can get in touch with the department that produced the dataset. This is a pilot project. We are in the process of adding a quality framework to make it easier for you to access high quality, reliable data.
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
The Harvard Dataverse Repository is a free data repository open to all researchers from any discipline, both inside and outside of the Harvard community, where you can share, archive, cite, access, and explore research data. Each individual Dataverse collection is a customizable collection of datasets (or a virtual repository) for organizing, managing, and showcasing datasets.
A research data repository for the education and developmental sciences.