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Found 96 result(s)
figshare allows researchers to publish all of their research outputs in an easily citable, sharable and discoverable manner. All file formats can be published, including videos and datasets. Optional peer review process. figshare uses creative commons licensing. figshare+ repository allows figshare users to share larger datasets, over 20GB up to many TBs, see: https://plus.figshare.com/
ZENODO builds and operates a simple and innovative service that enables researchers, scientists, EU projects and institutions to share and showcase multidisciplinary research results (data and publications) that are not part of the existing institutional or subject-based repositories of the research communities. ZENODO enables researchers, scientists, EU projects and institutions to: easily share the long tail of small research results in a wide variety of formats including text, spreadsheets, audio, video, and images across all fields of science. display their research results and get credited by making the research results citable and integrate them into existing reporting lines to funding agencies like the European Commission. easily access and reuse shared research results.
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
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The USACH research data repository provides a platform for researchers affiliated to the University to share, manage and preserve research data. So that they are accessible and detectable, both for the internal and external community, bringing the knowledge generated closer to the population.
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WueData is the institutional research data repository of the University of Würzburg. This service offered by the IT Center and the University Library enables scientists to publish their digital research data in accordance with the FAIR principles.
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RADAR4Chem is a low-threshold and easy-to use service for sustainable publication and preservation of research data from all disciplines of chemistry. It offers free publication for any data type and format according to the FAIR principles, independent of the researcher´s institutional affiliation. Through persistent identifiers (DOI) and a guaranteed retention period of at least 25 years, the research data remain available, citable and findable long-term. Currently, the offer is aimed exclusively at researchers in the field of chemistry at publicly funded research institutions and universities in Germany. No contract is required and no data publication fees are charged. The researchers are responsible for the upload, organisation, annotation and curation of research data as well as the peer-review process (as an optional step) and finally their publication.
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Macromolecular Xtallography Raw Data Repository (MX-RDR) is a domain-specific digital repository of crystallographic open research data. The use of Repository is open for everyone.
<<<!!!<<< Stated 2019-10-30: Dash is no longer available. Researchers are advised to store their research data at Dryad https://www.re3data.org/repository/r3d100000044 >>>!!!>>> Dash is an open data publication platform for upload, access, and re-use of research data. Submissions to Dash may be from researchers at participating UC campuses, researchers in earth science and ecology (DataONE), and researchers submitting to the UC Press journals Elementa and Collabra. Self-service depositing of research data through Dash fulfills publisher, funder, and data management plan requirements regarding data sharing and preservation. When researchers publish their datasets through Dash, their datasets are issued a DOI (DataCite) to optimize citability, and are publicly available for download and re-use under a CC BY 4.0 or CC-0 license. Deposited data are preserved in Merritt, California Digital Library’s preservation repository.
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SLGO is positioning itself as being the most complete and diversified source of scientific data regarding the St. Lawrence's ecosystem. It has done so by clustering and sharing information, data, and expertise from government, academic, and community agencies. SLGO offers a range of products such as data visualization applications, data management tools, and modeling products able to meet information needs for domains such as public safety, climate change, resource management, and biodiversity conservation. Available at SLGO.ca: observations, forecasts, predictions, and data archives
The Arctic Data Center is the primary data and software repository for the Arctic section of NSF Polar Programs. The Center helps the research community to reproducibly preserve and discover all products of NSF-funded research in the Arctic, including data, metadata, software, documents, and provenance that links these together. The repository is open to contributions from NSF Arctic investigators, and data are released under an open license (CC-BY, CC0, depending on the choice of the contributor). All science, engineering, and education research supported by the NSF Arctic research program are included, such as Natural Sciences (Geoscience, Earth Science, Oceanography, Ecology, Atmospheric Science, Biology, etc.) and Social Sciences (Archeology, Anthropology, Social Science, etc.). Key to the initiative is the partnership between NCEAS at UC Santa Barbara, DataONE, and NOAA’s NCEI, each of which bring critical capabilities to the Center. Infrastructure from the successful NSF-sponsored DataONE federation of data repositories enables data replication to NCEI, providing both offsite and institutional diversity that are critical to long term preservation.
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Fairdata IDA is a research data storage service that provides secure storage for research data. The Fairdata services are a group of nationally developed Finnish ICT services for managing research data, especially in the later phases of the research life cycle (sharing, publishing, and preserving). Development of research data management infrastructure has been identified as an important step in enabling implementation of the FAIR principles. The Fairdata services are funded by the Finnish Ministry of Education and Culture, and developed and maintained by CSC IT Center for Science. The services consist of the following service components: IDA – Research Data Storage; Etsin – Research Data Finder; Qvain – Research Dataset Metadata Tool; Metax – Metadata Warehouse; AVAA – Dynamic Data Publishing Platform and the Digital Preservation Service for Research Data (including management and packaging). The services also provide means for applying for and granting permits to use restricted access datasets. The service is offered free of charge for its users. The services are available to the research community in accordance with the applicable usage policy. Minedu offers access to research data storage service IDA to Finnish higher education institutions, state research institutes and projects funded by the Academy of Finland. Minedu may also grant separate access or storage capacity to the service. Finnish higher education institutions and research institutes may distribute IDA storage capacity to actors within the Finnish research system, within the limits of their usage shares. The service is intended for storing research data and materials related to it. The data stored in the service is available to all project users. The users mark their data to be persistently stored (“Frozen”) in the service. All project members may make the “Frozen” data and related metadata publicly accessible by using the other aforementioned Fairdata services. The data in the service is stored in Finland. IDA service stores the data stored by organisations projects continuously or until it’s transferred to digital preservation, provided that the Terms of Use are met. The owners of the data decide on the openness and usage policies for their own data. User organisations are offered support and guidance on using the service.
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The Universidad del Rosario Research data repository is an institutional iniciative launched in 2019 to preserve, provide access and promote the use of data resulting from Universidad del Rosario research projects. The Repository aims to consolidate an online, collaborative working space and data-sharing platform to support Universidad del Rosario researchers and their collaborators, and to ensure that research data is available to the community, in order to support further research and contribute to the democratization of knowledge. The Research data repository is the heart of an institutional strategy that seeks to ensure the generation of Findable, Accessible, Interoperable and Reusable (FAIR) data, with the aim of increasing its impact and visibility. This strategy follows the international philosophy of making research data “as open as possible and as closed as necessary”, in order to foster the expansion, valuation, acceleration and reusability of scientific research, but at the same time, safeguard the privacy of the subjects. The platform storage, preserves and facilitates the management of research data from all disciplines, generated by the researchers of all the schools and faculties of the University, that work together to ensure research with the highest standards of quality and scientific integrity, encouraging innovation for the benefit of society.
DMU Figshare is De Montfort University's institutional research data management platform. It showcases research from staff at the university.
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The nature of the ‘Bridge of Data’ project is to design and build a platform that allows collecting, searching, analyzing and sharing open research data and to provide it with unique data collected from the three most important Pomeranian universities: Gdańsk University of Technology, Medical University of Gdańsk and the University of Gdańsk. These data will be made available free of charge to the scientific community, entrepreneurs and the public. A bridge will be built to allow reuse of Open Research Data. The available research data will be described by standards developed by dedicated, experienced scientific teams. The metadata will allow other external computer systems to interpret the collected data. ORD descriptions will also include data reuse or reduction scenarios to facilitate further processing.