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Found 34 result(s)
>>>>!!!<<< As stated 2017-06-27 The website http://researchcompendia.org is no longer available; repository software is archived on github https://github.com/researchcompendia >>>!!!<<< The ResearchCompendia platform is an attempt to use the web to enhance the reproducibility and verifiability—and thus the reliability—of scientific research. we provide the tools to publish the "actual scholarship" by hosting data, code, and methods in a form that is accessible, trackable, and persistent. Some of our short term goals include: To expand and enhance the platform including adding executability for a greater variety of coding languages and frameworks, and enhancing output presentation. To expand usership and to test the ResearchCompendia model in a number of additional fields, including computational mathematics, statistics, and biostatistics. To pilot integration with existing scholarly platforms, enabling researchers to discover relevant Research Compendia websites when looking at online articles, code repositories, or data archives.
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DABAR (Digital Academic Archives and Repositories) is the key component of the Croatian e-infrastructure’s data layer. It provides technological solutions that facilitate maintenance of higher education and science institutions' digital assets, i.e., various digital objects produced by the institutions and their employees.
The AOML Environmental Data Server (ENVIDS) provides interactive, on-line access to various oceanographic and atmospheric datasets residing at AOML. The in-house datasets include Atlantic Expendable Bathythermograph (XBT), Global Lagrangian Drifting Buoy, Hurricane Flight Level, and Atlantic Hurricane Tracks (North Atlantic Best Track and Synoptic). Other available datasets include Pacific Conductivitiy/Temperature/Depth Recorder (CTD) and World Ocean Atlas 1998.
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Science Data Bank is an open generalist data repository developed and maintained by the Chinese Academy of Sciences Computing and Network Information Center (CNIC). It promotes the publication and reuse of scientific data. Researchers and journal publishers can use it to store, manage and share science data.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
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.
OSTI is the DOE office that collects, preserves, and disseminates DOE-sponsored R&D results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions. The information is typically in the form of technical documents, conference papers, articles, multimedia, and software, collectively referred to as scientific and technical information (STI).
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.
<<<!!!<<< This repository is no longer available>>>!!!>>>. Although the web pages are no longer available, you will still be able to download the final UniGene builds as static content from the FTP site https://ftp.ncbi.nlm.nih.gov/repository/UniGene/. You will also be able to match UniGene cluster numbers to Gene records by searching Gene with UniGene cluster numbers. For best results, restrict to the “UniGene Cluster Number” field rather than all fields in Gene. For example, a search with Mm.2108[UniGene Cluster Number] finds the mouse transthyretin Gene record (Ttr). You can use the advanced search page https://www.ncbi.nlm.nih.gov/gene/advanced to help construct these searches. Keep in mind that the Gene record contains selected Reference Sequences and GenBank mRNA sequences rather than the larger set of expressed sequences in the UniGene cluster.
Central data management of the USGS for water data that provides access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands. Includes data on water use and quality, groundwater, and surface water.
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depositar — taking the term from the Portuguese/Spanish verb for to deposit — is an online repository for research data. The site is built by the researchers for the researchers. You are free to deposit, discover, and reuse datasets on depositar for all your research purposes.
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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.
OLOS is a Swiss-based data management portal tailored for researchers and institutions. Powerful yet easy to use, OLOS works with most tools and formats across all scientific disciplines to help researchers safely manage, publish and preserve their data. The solution was developed as part of a larger project focusing on Data Life Cycle Management (dlcm.ch) that aims to develop various services for research data management. Thanks to its highly modular architecture, OLOS can be adapted both to small institutions that need a "turnkey" solution and to larger ones that can rely on OLOS to complement what they have already implemented. OLOS is compatible with all formats in use in the different scientific disciplines and is based on modern technology that interconnects with researchers' environments (such as Electronic Laboratory Notebooks or Laboratory Information Management Systems).
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It is a statistical system developed for collection, computerization, analysis and use of educational and allied data for planning, management, monitoring and feedback. So, DISE is an initiative of the Department of Educational Management Information System (EMIS) of NUEPA for developing and strengthening the educational management information system in India. The initiative is coordinated from district level to state and extended up to national level are being constantly collected and disseminated. It provides information on vital parameters relating to students, teachers and infrastructure at all levels of education in India. Presently DISE has three modules U-DISE, DISE, and SEMIS. DISE also provides several other derivative statistical products, such as, District Report Cards, State Report Cards, School Report Cards, Flash Statistics, Analytical Reports, Rural/Urban Statistics, etc.
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The CORA. Repositori de dades de Recerca is a repository of open, curated and FAIR data that covers all academic disciplines. CORA. Repositori de dades de Recerca is a shared service provided by participating Catalan institutions (Universities and CERCA Research Centers). The repository is managed by the CSUC and technical infrastructure is based on the Dataverse application, developed by international developers and users led by Harvard University (https://dataverse.org).
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.
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Research Data Australia is the data discovery service of the Australian Research Data Commons (ARDC). The ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program. Research Data Australia helps you find, access, and reuse data for research from over one hundred Australian research organisations, government agencies, and cultural institutions. We do not store the data itself here but provide descriptions of, and links to, the data from our data publishing partners.
Europeana is the trusted source of cultural heritage brought to you by the Europeana Foundation and a large number of European cultural institutions, projects and partners. It’s a real piece of team work. Ideas and inspiration can be found within the millions of items on Europeana. These objects include: Images - paintings, drawings, maps, photos and pictures of museum objects Texts - books, newspapers, letters, diaries and archival papers Sounds - music and spoken word from cylinders, tapes, discs and radio broadcasts Videos - films, newsreels and TV broadcasts All texts are CC BY-SA, images and media licensed individually.