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Found 39 result(s)
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
The Spiral Digital Repository is the Imperial College London institutional open access repository. This system allows you, as an author, to make your research documents open access without incurring additional publication costs. When you self-archive a research document in Spiral it becomes free for anyone to read. You can upload copies of your publications to Spiral using Symplectic Elements. All deposited content becomes searchable online.
The Global Hydrology Resource Center (GHRC) provides both historical and current Earth science data, information, and products from satellite, airborne, and surface-based instruments. GHRC acquires basic data streams and produces derived products from many instruments spread across a variety of instrument platforms.
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Research Data Finder is QUT’s discovery service for research data created or collected by QUT researchers. Designed to promote the visibility of QUT research datasets, Research Data Finder provides descriptions about shareable, reusable datasets available via open or mediated access.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
Merritt is a curation repository for the preservation of and access to the digital research data of the ten campus University of California system and external project collaborators. Merritt is supported by the University of California Curation Center (UC3) at the California Digital Library (CDL). While Merritt itself is content agnostic, accepting digital content regardless of domain, format, or structure, it is being used for management of research data, and it forms the basis for a number of domain-specific repositories, such as the ONEShare repository for earth and environmental science and the DataShare repository for life sciences. Merritt provides persistent identifiers, storage replication, fixity audit, complete version history, REST API, a comprehensive metadata catalog for discovery, ATOM-based syndication, and curatorially-defined collections, access control rules, and data use agreements (DUAs). Merritt content upload and download may each be curatorially-designated as public or restricted. Merritt DOIs are provided by UC3's EZID service, which is integrated with DataCite. All DOIs and associated metadata are automatically registered with DataCite and are harvested by Ex Libris PRIMO and Thomson Reuters Data Citation Index (DCI) for high-level discovery. Merritt is also a member node in the DataONE network; curatorially-designated data submitted to Merritt are automatically registered with DataONE for additional replication and federated discovery through the ONEMercury search/browse interface.
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Rodare is the institutional research data repository at HZDR (Helmholtz-Zentrum Dresden-Rossendorf). Rodare allows HZDR researchers to upload their research software and data and enrich those with metadata to make them findable, accessible, interoperable and retrievable (FAIR). By publishing all associated research software and data via Rodare research reproducibility can be improved. Uploads receive a Digital Object Identfier (DOI) and can be harvested via a OAI-PMH interface.
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 range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
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An institutional repository at Graz University of Technology to enable storing, sharing and publishing research data, publications and open educational resources. It provides open access services and follows the FAIR principles.
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The National High Energy Physics Science Data Center (NHEPSDC) is a repository for high-energy physics. In 2019, it was designated as a scientific data center at the national level by the Ministry of Science and Technology of China (MOST). NHEPSDC is constructed and operated by the Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences (CAS). NHEPSDC consists of a main data center in Beijing, a branch center in Guangdong-Hong Kong-Macao Greater Bay Area, and a branch center in Huairou District of Beijing. The mission of NHEPSDC is to provide the services of data collection, archiving, long-term preservation, access and sharing, software tools, and data analysis. The services of NHEPSDC are mainly for high-energy physics and related scientific research activities. The data collected can be roughly divided into the following two categories: one is the raw data from large scientific facilities, and the other is data generated from general scientific and technological projects (usually supported by government funding), hereafter referred to as generic data. More than 70 people work in NHEPSDC now, with 18 in high-energy physics, 17 in computer science, 15 in software engineering, 20 in data management and some other operation engineers. NHEPSDC is equipped with a hierarchical storage system, high-performance computing power, high bandwidth domestic and international network links, and a professional service support system. In the past three years, the average data increment is about 10 PB per year. By integrating data resources with the IT environment, a state-of-art data process platform is provided to users for scientific research, the volume of data accessed every year is more than 400 PB with more than 10 million visits.
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.
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Jülich DATA is a registry service to index all research data created at or in the context of Forschungszentrum Jülich. As an institutionial repository, it may also be used for data and software publications.
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.
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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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Repository of the Faculty of Science is institutional repository that gathers, permanently stores and allows access to the results of scientific and intellectual property of the Faculty of Science, University of Zagreb. The objects that can be stored in the repository are research data, scientific articles, conference papers, theses, dissertations, books, teaching materials, images, video and audio files, and presentations. To improve searchability, all materials are described with predetermined set of metadata.
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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.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
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ISTA Research Explorer is an online digital repository of multi-disciplinary research datasets as well as publications produced at IST Austria, hosted by the Library. ISTA researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researches, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.
UltraViolet is part of a suite of repositories at New York University that provide a home for research materials, operated as a partnership of the Division of Libraries and NYU IT's Research and Instruction Technology. UltraViolet provides faculty, students, and researchers within our university community with a place to deposit scholarly materials for open access and long-term preservation. UltraViolet also houses some NYU Libraries collections, including proprietary data collections.
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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.
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.