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Found 270 result(s)
The FAIRDOMHub is built upon the SEEK software suite, which is an open source web platform for sharing scientific research assets, processes and outcomes. FAIRDOM (Web Site) will establish a support and service network for European Systems Biology. It will serve projects in standardizing, managing and disseminating data and models in a FAIR manner: Findable, Accessible, Interoperable and Reusable. FAIRDOM is an initiative to develop a community, and establish an internationally sustained Data and Model Management service to the European Systems Biology community. FAIRDOM is a joint action of ERA-Net EraSysAPP and European Research Infrastructure ISBE.
The Society of American Archivists (SAA) Dataverse is an SAA data service that was established to support the needs and interests of SAA’s members and the broader archives community. The SAA Dataverse supports the reuse of datasets for purposes of fostering knowledge, insights, and a deeper understanding of archival organizations, the status of archivists, and the impact of archives and archival work on the broader society. Deposited datasets should be “actionable” in that they should support direct analysis and interpretation. The SAA Dataverse welcomes deposits of collections of quantitative or qualitative data and associated documentation. SAA membership is not required to deposit or use data in the SAA Dataverse.
The Perovskite Database Project aims at making all perovskite device data, both past and future, available in a form adherent to the FAIR data principles, i.e. findable, accessible, interoperable, and reusable.
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Macquarie University's Institutional Research Data Repository (RDR) allows researchers to upload, publish, search and download research data. The RDR promotes collaboration, data sharing and discovery amongst researchers globally according to FAIR data principles. The RDR is based on Figshare for Institutions, which has been specifically tailored to suit the needs of the Macquarie University research community.
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Tallinn University of Technology Data Repository (TalTechData) is a storage space for researchers to deposit data sets associated with their research. The main goal of TalTechData is to gather all fields of research data and encouraging open science and FAIR principles (Findable, Accessible, Interoperable and Reusable). Through preserving open research data TalTechData enriches academic quality and collaboration, supports innovative developments and supports overall use of scientific materials.
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The institutional research data repository of the Universität Innsbruck is a service to enable storing, sharing and publishing of research data according to the FAIR principles for its employees and project partners.
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The Research Data Repository is a technological infrastructure that allows the preservation and access to research data produced at Universidad Andrés Bello (Chile). The repository complies with international standards for the deposit and access of data, highlighting the FAIR principles. These principles guarantee that the data will be Findable, Accessible, Interoperable and Reusable.
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nmrXiv is an open, FAIR and consensus-driven NMR spectroscopy data repository and analysis platform. We archive raw and processed NMR data, providing support for browsing, search, analysis, and dissemination of NMR data worldwide.
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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.
Science Photo Library (SPL) provides creative professionals with striking specialist imagery, unrivalled in quality, accuracy and depth of information. We have more than 600,000 images and 40,000 clips to choose from, with hundreds of new submissions uploaded to the website each week.
Data products developed and distributed by the National Institute of Standards and Technology span multiple disciplines of research and are widely used in research and development programs by industry and academia. NIST's publicly available data sets showcase its committment to providing accurate, well-curated measurements of physical properties, exemplified by the Standard Reference Data program, as well as its committment to advancing basic research. In accordance with U.S. Government Open Data Policy and the NIST Plan for providing public access to the results of federally funded research data, NIST maintains a publicly accessible listing of available data, the NIST Public Dataset List (json). Additionally, these data are assigned a Digital Object Identifier (DOI) to increase the discovery and access to research output; these DOIs are registered with DataCite and provide globally unique persistent identifiers. The NIST Science Data Portal provides a user-friendly discovery and exploration tool for publically available datasets at NIST. This portal is designed and developed with data.gov Project Open Data standards and principles. The portal software is hosted in the usnistgov github repository.
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The Canadian VirusSeq Data Portal (CVDP) is an open-access data portal funded by Genome Canada. It is intended to facilitate access to Canadian SARS-CoV-2 sequences and associated non-sensitive metadata adhering to the FAIR Data principles. Limited contextual metadata and viral genome sequences can be shared among Canadian public health labs, researchers and other groups interested in accessing the data for surveillance, research, and innovation purposes. The CVDP will harmonize, validate, and automate submission to international databases and enable the creation of real-time dashboards that summarize the Canadian data contributions while facilitating exploration and access. Sequences or metadata submitted to the CVDP may not include data that could reveal the personal identity of the source. Its is part of Canadian COVID Genomics Network (CanCOGeN).
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Portal Zarządzania Wiedzą UJ CM is a knowledge and research potential management platform of medical information. Easy data localization will be possible thanks to DOI and URL addresses given by administrators of the Knowledge Management Platform JU MC. The data will be stored in 2 copies for 10 years.
ODC-TBI is a community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Traumatic Brain Injury research through sharing of data from basic and clinical research.
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PsychArchives is a disciplinary repository for psychological science and neighboring disciplines. Accommodating 20 different digital research object (DRO) types, including articles, preprints, research data, code, supplements, preregistrations, tests and multimedia objects, PsychArchives provides a digital space that integrates all research-related content relevant to psychology. PsychArchives is committed to the FAIR principles, facilitating the findability, accessibility, interoperability and reusability of research and research data.
FAIR & long-term storage of research data from computational materials science, or from experimental materials science that is of relevance to simulations. Complementary tools available to explore the full provenance of the calculations and to perform simulations or data analytics in the cloud.
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
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FDAT is a research data repository hosted by the University of Tübingen, designed to facilitate long-term archiving and publication of research data. Managed by the Information, Communication and Media Center (IKM), it primarily caters to the humanities and social sciences, while welcoming researchers from all scientific disciplines at the university. Committed to high-quality data management, FDAT emphasizes the importance of adhering to the FAIR Data Principles, promoting findability, accessibility, interoperability, and reusability of the research data it contains.
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.
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'Redape' is a digital repository that aims to preserve and disseminate research data produced by the Brazilian Agricultural Research Corporation - Embrapa. It allows the organization, management and publication of data in accordance with the FAIR principles.
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The NOMAD Repository and Archive stands for open access of scientific materials data. It enables the confirmatory analysis of materials data, their reuse, and repurposing. All data is available in their raw format as produced by the underlying code (Repository) and in a common, machine-processable, and well-defined data format (Archive).
The Johns Hopkins Research Data Repository is an open access repository for Johns Hopkins University researchers to share their research data. The Repository is administered by professional curators at JHU Data Services, who will work with depositors to enable future discovery and reuse of your data, and ensure your data is Findable, Accessible, Interoperable and Reusable (FAIR). More information about the benefits of archiving data can be found here: https://dataservices.library.jhu.edu/