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Found 7 result(s)
From now on you no longer deposit archaeological data here in EASY . Please see: https://archaeology.datastations.nl/ EASY is the online archiving system of Data Archiving and Networked Services (DANS). EASY offers you access to thousands of datasets in the humanities, the social sciences and other disciplines. EASY can also be used for the online depositing of research data.
UCLA Library is adopting Dataverse, the open source web application designed for sharing, preserving and using research data. UCLA Dataverse will allow data, text, software, scripts, data visualizations, etc., created from research projects at UCLA to be made publicly available, widely discoverable, linkable, and ultimately, reusable
Country
To target the multidisciplinary, broad scale nature of empirical educational research in the Federal Republic of Germany, a networked research data infrastructure is required which brings together disparate services from different research data providers, delivering services to researchers in a usable, needs-oriented way. The Verbund Forschungsdaten Bildung (Educational Research Data Alliance, VFDB) therefore aims to cooperate with relevant actors from science, politics and research funding institutes to set up a powerful infrastructure for empirical educational research. This service is meant to adequately capture specific needs of the scientific communities and support empirical educational research in carrying out excellent research.
Country
Discuss Data is an open repository for storing, sharing and discussing research data on Eastern Europe, the South Caucasus and Central Asia. The platform, launched in September 2020, is funded by the German Research Foundation (DFG) and operated by the Research Centre for East European Studies at the University of Bremen (FSO) and the Göttingen State and University Library (SUB). Discuss Data goes beyond ordinary repositories and offers an interactive online platform for the discussion and quality assessment of research data. Our aim is to create a space for academic communication and for the community-specific publication, curation, annotation and discussion of research data.
Open access repository for digital research created at the University of Minnesota. U of M researchers may deposit data to the Libraries’ Data Repository for U of M (DRUM), subject to our collection policies. All data is publicly accessible. Data sets submitted to the Data Repository are reviewed by data curation staff to ensure that data is in a format and structure that best facilitates long-term access, discovery, and reuse.
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.