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Found 26 result(s)
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SMU Research Data Repository (SMU RDR) is a tool and service for researchers from Singapore Management University (SMU) to store, share and publish their research data. SMU RDR accepts a wide range of research data and outputs generated from research projects.
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Ktisis is an open access institutional repository gathering any digital material relating to the various activities of the Cyprus University of Technology, especially original research material produced by the members of the University. Defined in this framework, Ktisis demonstrates the intellectual life and the research activities of the University, preserving, spreading and promoting the scientific research to the local and international community. Ktisis was named after the symbol of the Cyprus University of Technology depicting Ktisis, the spirit of creation.
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PTB is the national metrology institute of the Federal Republic of Germany. The Open Access Repository of the Physikalisch-Technische Bundesanstalt grants free access to a number of factual datasets and documents that were elaborated at PTB. This includes publications such as the "PTB-Mitteilungen", the metrological expert journal of PTB, and numerous of documents from the field of legal metrology.
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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.
The Centre for the Environment, Fisheries and Aquaculture Science (Cefas), as one of the world's longest-established marine research organisations, has provided advice on the sustainable exploitation of marine resources since 1902. Today Cefas works in support of a healthy environment and a growing blue economy providing innovative solutions for the aquatic environment, biodiversity and food security. The Cefas Data Hub provides access to over 2080 metadata records, with over 5500 data sets available to download and connect to in support of commitments to Open Science through the Data Portal. Datasets available are increasingly diverse and include many legacy datasets including those from fish, shellfish and plankton surveys from the 1980's to the present day. Other increasingly international datasets made available include species migration data from tagging activities and data on habitat and sediment, ecosystem change, human activities including marine litter, otolith sampling and fish stomach contents, oceanography, acoustics, health and water quality. Data is provided under Open Government License by default where feasible.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
Discovery is the digital repository of research, and related activities, undertaken at the University of Dundee. The content held in Discovery is varied and ranges from traditional research outputs such as peer-reviewed articles and conference papers, books, chapters and post-graduate research theses and data to records for artefacts, exhibitions, multimedia and software. Where possible Discovery provides full-text access to a version of the research. Discovery is the data catalogue for datasets resulting from research undertaken at the University of Dundee and in some instances the publisher of research data.
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DAIS - Digital Archive of the Serbian Academy of Sciences and Arts is a joint digital repository of the Serbian Academy of Sciences and Arts (SASA) and the research institutes under the auspices of SASA. The aim of the repository is to provide open access to publications and other research outputs resulting from the projects implemented by the SASA and its institutes. The repository uses a DSpace-based software platform developed and maintained by the Belgrade University Computer Centre (RCUB).
Constellation is a digital object identifier (DOI) based science network for supercomputing data. Constellation makes it possible for OLCF researchers to obtain DOIs for large data collections by tying them together with the associated resources and processes that went into the production of the data (e.g., jobs, collaborators, projects), using a scalable database. It also allows the annotation of the scientific conduct with rich metadata, and enables the cataloging and publishing of the artifacts for open access, aiding in scalable data discovery. OLCF users can use the DOI service to publish datasets even before the publication of the paper, and retain key data even after project expiration. From a center standpoint, DOIs enable the stewardship of data, and better management of the scratch and archival storage.
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Yale-NUS Dataverse is the institutional research data repository of Yale-NUS College. The goals of Yale-NUS Dataverse are to collect, preserve and showcase the research output of Yale-NUS researchers and through this, increase the research visibility of Yale-NUS researchers and demonstrate the research excellence of Yale-NUS College to the world.
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The INESC TEC data repository showcases datasets produced or used by INESC TEC researchers and their partners. The repository is organized in four groups (institutional clusters). Computer Science, Power and Energy, Network and Intelligent Systems and Power and Energy.