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Found 371 result(s)
Country
DaRUS, the data repository of the University of Stuttgart, offers a secure location for research data and codes, be it for the administration of own data, for exchange within a research group, for sharing with selected partners or for publishing.
The SURF Data Repository is a user-friendly web-based data publication platform that allows researchers to store, annotate and publish research datasets of any size to ensure long-term preservation and availability of their data. The service allows any dataset to be stored, independent of volume, number of files and structure. A published dataset is enriched with complex metadata, unique identifiers are added and the data is preserved for an agreed-upon period of time. The service is domain-agnostic and supports multiple communities with different policy and metadata requirements.
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Built on the Islandora digital repository framework, the UPEI hosted Published and Archived Data (data.upei.ca) service provides researchers with a place to securely publish or archive their research datasets.
The aim of the project is systematic mapping of Czech and other languages in comparison with Czech. CNC corpora are accessible to everybody interested in studying the language after free registration.
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Phaidra (Permanent Hosting, Archiving and Indexing of Digital Resources and Assets) is the University of Padua Library System’s platform for long-term archiving of digital collections. Phaidra hosts various types of digital objects (antiquarian books, manuscripts, photographs, wallcharts, maps, learning objects, films, archive material and museum objects). Phaidra offers a search facility to identify specific objects, and each object can be viewed, downloaded, used and reused to the extent permitted by law and by its associated licences. The objects in the digital collections on the Phaidra platform are sourced from libraries (in large part due to the digitisation projects promoted by the Library System itself), museums and archives at the University of Padua and other institutions, including the Ca’ Foscari University and the Università Iuav in Venice.
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The Goethe University Data Repository (GUDe) provides a platform for its members to electronically archive, share, and publish their research data. GUDe is jointly operated by the University Library and the University Data Center of the Goethe University. The metadata of all public content is freely available and indexed by search engines as well as scientific web services. GUDe follows the FAIR principles for long-term accessibility (minimum 10 years), allows for reliable citation via DOIs as well as cooperative access to non-public data and operates on DSpace-CRIS v7. If you have any questions regarding the use of GUDe, please consult the user documentation.
TiU Dataverse is the central online repository for research data at Tilburg University. The TiU Dataverse is managed by the Research Data Office (RDO) at Library and IT Services (LIS). TiU Dataverse takes part of the DataverseNL network. DataverseNL is a shared data service of several Dutch universities and institutions. The data management is in the hands of the member organizations, while the national organization Data Archiving and Networked Services (DANS) manages the network
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The UWA Profiles and Research Repository contains research publications, research datasets, theses, equipment, grants and activities created by researchers and postgraduates affiliated with the University of Western Australia (UWA). It is managed by the University Library and provides access to research datasets held at UWA. The information about each dataset has been provided by UWA research groups. Dataset metadata is harvested into Research Data Australia (RDA) https://researchdata.edu.au/.
The Archaeological Map of the Czech Republic (AMCR) is a repository designed for information on archaeological investigations, sites and finds, operated by the Archaeological Institutes of the CAS in Prague and Brno. The archives of these institutions contain documentation of archaeological fieldwork on the territory of the Czech Republic from 1919 to the present day, and they continue to enrich their collections. The AMCR database and related documents form the largest collection of archaeological data concerning the Czech Republic and are therefore an important part of our cultural heritage. The AMCR digital archive contains various types of records - individual archaeological documents (texts, field photographs, aerial photographs, maps and plans, digital data), projects, fieldwork events, archaeological sites, records of individual finds and a library of 3D models. Data and descriptive information are continuously taken from the AMCR and presented in the the AMCR Digital Archive interface.
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Figshare has been chosen as the University of Adelaide's official data and digital object repository with unlimited local storage. All current staff and HDR students can access and publish research data and digital objects on the University of Adelaide's Figshare site. Because Figshare is cloud-based, you can access it anywhere and at any time.
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GAMS is an OAIS compliant asset management system for the management, publication and long-term archiving of digital resources from the Humanities. It enables scholars, researchers and students to manage and publish resources from projects with permanent identification and enriched with metadata.
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The portal that allows you, in a centralized way, to search and access all the primary research data sets available in open access through the institutional digital repositories that make up the Sistema Nacional de Repositorios Digitales (SNRD)
The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.
Yareta is a repository service built on digital solutions for archiving, preserving and sharing research data that enable researchers and institutions of any disciplines to share and showcase their research results. The solution was developed as part of a larger project focusing on Data Life Cycle Management (dlcm.ch) that aims to develop various services for research data management. Thanks to its highly modular architecture, Yareta can be adapted both to small institutions that need a "turnkey" solution and to larger ones that can rely on Yareta to complement what they have already implemented. Yareta is compatible with all formats in use in the different scientific disciplines and is based on modern technology that interconnects with researchers' environments (such as Electronic Laboratory Notebooks or Laboratory Information Management Systems).
Yoda is a research data management service that enables researchers to deposit, share, publish and preserve large amounts of research data during all stages of a research project. This service is managed and supported by an interdisciplinary team of university employees. The software has been developed at Utrecht University and is used by multiple organisations, both in the Netherlands and abroad. Yoda publishes data packages via Datacite. To find data publications use: https://public.yoda.uu.nl/, or the Datacite search engine: https://commons.datacite.org/doi.org?query=client.uid:delft.uu
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Didόmena is the platform that enables EHESS research units to organize, share and perpetuate the data used or produced as part of their work. Data are described according to scientific and technical information standards. The Didόmena publication is primarily intended to illustrate or support published results; but it also makes it possible to reuse of data in other research projects and, more generally access to data for all those interested in social science research.
DataON is Korea's National Research Data Platform. It provides integrated search of metadata for KISTI's research data and domestic and international research data and links to raw data. DataON allows users (researchers, policy makers, etc.) to perform the following tasks: Easily search for various types of research data in all scientific fields. By registering research results, research data can be posted and cited. Build a community among researchers and enable collaborative research. It provides a data analysis environment that allows one-stop analysis of discovered research data.
B2SHARE is a user-friendly, reliable and trustworthy way for researchers, scientific communities and citizen scientists to store and share small-scale research data from diverse contexts and disciplines. B2SHARE is able to add value to your research data via (domain tailored) metadata, and assigning citable Persistent Identifiers PIDs (Handles) to ensure long-lasting access and references. B2SHARE is one of the B2 services developed via EUDAT and long tail data deposits do not cost money. Special arrangements such as branding and special metadata elements can be made on request.
IDEALS is an institutional repository that collects, disseminates, and provides persistent and reliable access to the research and scholarship of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students, and in some cases undergraduate students, can deposit their research and scholarship directly into IDEALS. Departments can use IDEALS to distribute their working papers, technical reports, or other research material. Contact us at https://www.ideals.illinois.edu/feedback for more information.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.