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Found 21 result(s)

Mendeley Data

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For datasets big and small; Store your research data online. Quickly and easily upload files of any type and we will host your research data for you. Your experimental research data will have a permanent home on the web that you can refer to.

Duke Research Data Repository

Duke RDR

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The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.

Inspire-HEP

Inspire-High Energy Physics

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CERN, DESY, Fermilab and SLAC have built the next-generation High Energy Physics (HEP) information system, INSPIRE. It combines the successful SPIRES database content, curated at DESY, Fermilab and SLAC, with the Invenio digital library technology developed at CERN. INSPIRE is run by a collaboration of CERN, DESY, Fermilab, IHEP, IN2P3 and SLAC, and interacts closely with HEP publishers, arXiv.org, NASA-ADS, PDG, HEPDATA and other information resources. INSPIRE represents a natural evolution of scholarly communication, built on successful community-based information systems, and provides a vision for information management in other fields of science.

OSF - Vrije Universiteit Amsterdam

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A Research Data Management Tool for the Vrije Universiteit Amsterdam Research Community.

DataverseNO

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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.

University of Warsaw Research Data Repository

Dane Badawcze Uniwersytetu Warszawskiego. Repozytorium

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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.

Edmond

The Open Research Data Repository of the Max Planck Society

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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.

TU Graz Repository

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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.

Jülich DATA

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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.

Repository of the Faculty of Science

Repository of the Faculty of Science of the University of Zagreb

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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.

osnaData

Das Forschungsdatenrepositorium der Universität Osnabrück

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osnaData, the institutional research data repository of the Osnabrück University, offers all members of the university the opportunity to publish their scientific research data free of charge and thus share it with the public in accordance with open science. Research data of all types and formats can be published and provided with appropriate licenses. osnaData assigns DOIs to datasets as persistent identifiers.

CORA. Repositori de Dades de Recerca

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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).

Climate Hazards Center Data Archive

CHC Data Archive

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Using a combination of remote sensing data and ground observations as inputs, CHC scientists have developed rainfall estimation techniques and other resources to support drought monitoring and predict crop performance in parts of the world vulnerable to crop failure. Policymakers within governments and non-governmental organizations rely on CHC decision-support products to make critical resource allocation decisions. The CHC's scientific focus is "geospatial hydroclimatology," with an emphasis on the early detection and forecasting of hydroclimatic hazards related to food-security droughts and floods. Basic research seeks an improved understanding of the climatic processes that govern drought and flood hazards in FEWS NET countries (https://fews.net/). The CHC develops better techniques, algorithms, and modeling applications in order to use remote sensing and other geospatial data for hazards early warning.

IZTECH GCRIS

İYTE GCRIS

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GCRIS Database is a research and performance evaluation information system that enables searching and discovering all research outputs within the Izmir Institute of Technology research ecosystem, associating these outputs with researchers, providing advanced reporting with different metrics, and supporting corporate strategic decisions. Besides, it is an institutional repository at international standards that brings together and organizes all kinds of academic outputs related to research activities and allows sharing with the whole scientific world by providing long-term preservation.

RODBUK Cracow Open Research Data Repository

RODBUK

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RODBUK Cracow Open Research Data Repository is co-created by six Cracow universities: AGH University of Science and Technology, University of Physical Education in Krakow, Cracow University of Technology, Krakow University of Economics, Jagiellonian University in Kraków, Pedagogical University of Krakow. The purpose of RODBUK is to collect, develop, archive and make available in open access all types of research data created by researchers, PhD candidates and students in the course of scientific activity. RODBUK aims to implement the Open Science policy by creating a publicly available platform for depositing research datasets enabling: getting acquainted with the research conducted in Cracow's scientific centers, storage of various types of research data obtaining a permanent Digital Object Identifier (DOI) for each dataset, standardized data citation, choosing a data usage license agreement (Creative Commons or other. RODBUK allows to collect and share open research data from various disciplines and in all file formats. RODBUK applies the FAIR Principles, which means the data is findable, accessible, interoperable, reusable.

TROLLing

Tromsø Repository of Language and Linguistics

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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/).

VecNet

Vector-Borne Disease Network

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<<<!!!<<< The repository is no longer available. 2019-09-06: no more access to VecNet >>>!!!>>>

DRYAD

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Dryad is an open data publishing platform and a community committed to the open availability and routine re-use of all research data. We publish data in any format and any discipline. All Dryad data undergoes a curation process and is published under a CC0 waiver to promote reuse.

DesignSafe-CI Data Depot Repository

A Repository Infrastructure for Natural Hazards Datasets

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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.

Repository for Open Data (RepOD)

Repository for Open 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.

OpenML

Open Machine Learning

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OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.