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Found 29 result(s)
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
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Welcome to the National Yang Ming Chiao Tung University Dataverse research data knowledge management website, where you can learn how to obtain, upload, cite and explore research data in the National Yang Ming Chiao Tung University Dataverse.
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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.
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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.
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 Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
CLARIN-LV is a national node of Clarin ERIC (Common Language Resources and Technology Infrastructure). The mission of the repository is to ensure the availability and long­ term preservation of language resources. The data stored in the repository are being actively used and cited in scientific publications.
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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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.
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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.
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RADAR4Culture is a low-threshold and easy-to use service for sustainable publication and preservation of cultural heritage research data. 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 at publicly funded research institutions and (art) universities as well as non-commercial academies, galleries, libraries, archives and museums 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.
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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RepOD is a general-purpose repository for open research data, offering all members of the academic community in Poland the possibility to deposit their work. It is intended for scientific data from all disciplines of knowledge and in all formats. The purpose of RepOD is to create a place where research data can be safely stored and openly shared with others.
BOARD (Bicocca Open Archive Research Data) is the institutional data repository of the University of Milano-Bicocca. BOARD is an open, free-to-use research data repository, which enables members of University of Milano-Bicocca to make their research data publicly available. By depositing their research data in BOARD researchers can: - Make their research data citable - Share their data privately or publicly - Ensure long-term storage for their data - Keep access to all versions - Link their article to their data
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PubData is Leuphana's institu­tional research data reposi­tory for the long-term preser­vation, documen­tation and publi­cation of research data from scienti­fic projects. PubData is main­tained by Leuphana's Media and Infor­mation Centre (MIZ) and is free of charge. The service is primarily aimed at Leuphana em­ployees and additionally at re­searchers from coope­ration partners con­tractually asso­ciated with Leuphana.
LINDAT/CLARIN is designed as a Czech “node” of Clarin ERIC (Common Language Resources and Technology Infrastructure). It also supports the goals of the META-NET language technology network. Both networks aim at collection, annotation, development and free sharing of language data and basic technologies between institutions and individuals both in science and in all types of research. The Clarin ERIC infrastructural project is more focused on humanities, while META-NET aims at the development of language technologies and applications. The data stored in the repository are already being used in scientific publications in the Czech Republic. In 2019 LINDAT/CLARIAH-CZ was established as a unification of two research infrastructures, LINDAT/CLARIN and DARIAH-CZ.
The Tromsø Repository of Language and Linguistics (TROLLing) is a FAIR-aligned repository of linguistic data and statistical code. The archive is open access, which means that all information is available to everyone. All data are accompanied by searchable metadata that identify the researchers, the languages and linguistic phenomena involved, the statistical methods applied, and scholarly publications based on the data (where relevant). Linguists worldwide are invited to deposit data and statistical code used in their linguistic research. TROLLing is a special collection within DataverseNO (http://doi.org/10.17616/R3TV17), and C Centre within CLARIN (Common Language Resources and Technology Infrastructure, a networked federation of European data repositories; http://www.clarin.eu/), and harvested by their Virtual Language Observatory (VLO; https://vlo.clarin.eu/).
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
The focus of PolMine is on texts published by public institutions in Germany. Corpora of parliamentary protocols are at the heart of the project: Parliamentary proceedings are available for long stretches of time, cover a broad set of public policies and are in the public domain, making them a valuable text resource for political science. The project develops repositories of textual data in a sustainable fashion to suit the research needs of political science. Concerning data, the focus is on converting text issued by public institutions into a sustainable digital format (TEI/XML).
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/