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Found 617 result(s)
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
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FDAT is a research data repository hosted by the University of Tübingen, designed to facilitate long-term archiving and publication of research data. Managed by the Information, Communication and Media Center (IKM), it primarily caters to the humanities and social sciences, while welcoming researchers from all scientific disciplines at the university. Committed to high-quality data management, FDAT emphasizes the importance of adhering to the FAIR Data Principles, promoting findability, accessibility, interoperability, and reusability of the research data it contains.
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HISTAT (Historical Statistics)provides data from studies of population, economic and social history as well as the historical Statistics under a single user interface to be made available online. HISTAT offers a variety of time series, Historical Statistics primarily from Germany, partly down to the 16 . century; the database is structured theme-and study-oriented. Studies are listed by subject area and can be individually selected. using an alphabetical list of authors of individual studies can also be selected. Moreover, a study on cross Keyword is offered. HISTAT provides information and research opportunities to both study level as well as at time series level. It offered a thesaurus-based meta-search for words, authors and studies in the study descriptions, the data (time series definitions) and the sources.
The South African Environmental Observation Network (SAEON) Open Data Platform (ODP) is a metadata repository that facilitates the publication, discovery, dissemination, and preservation of earth observation and environmental data in South Africa. SAEON is a long-term environmental observation and research facility of the National Research Foundation (NRF).
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Created and managed by the Library, DataSpace@HKUST is the data repository and workspace service for HKUST research community. Faculty members and research postgraduate students can use the platform to store, share, organize, preserve and publish research data. It is built on Dataverse, an open source web application developed at Harvard’s Institute for Quantitative Social Science. Using Dataverse architecture, the repository hosts multiple "dataverses". Each dataverse contains datasets; while each dataset may contain multiple data files and the corresponding descriptive metadata.
Cocoon "COllections de COrpus Oraux Numériques" is a technical platform that accompanies the oral resource producers, create, organize and archive their corpus; a corpus can consist of records (usually audio) possibly accompanied by annotations of these records. The resources registered are first cataloged and stored while, and then, secondly archived in the archive of the TGIR Huma-Num. The author and his institution are responsible for filings and may benefit from a restricted and secure access to their data for a defined period, if the content of the information is considered sensitive. The COCOON platform is jointly operated by two joint research units: Laboratoire de Langues et civilisations à tradition orale (LACITO - UMR7107 - Université Paris3 / INALCO / CNRS) and Laboratoire Ligérien de Linguistique (LLL - UMR7270 - Universités d'Orléans et de Tours, BnF, CNRS).
The BGS is a data-rich organisation with over 400 datasets in its care; including environmental monitoring data, digital databases, physical collections (borehole core, rocks, minerals and fossils), records and archives. Our data is managed by the National Geoscience Data Centre.
The Wolfram Data Repository is a public resource that hosts an expanding collection of computable datasets, curated and structured to be suitable for immediate use in computation, visualization, analysis and more. Building on the Wolfram Data Framework and the Wolfram Language, the Wolfram Data Repository provides a uniform system for storing data and making it immediately computable and useful. With datasets of many types and from many sources, the Wolfram Data Repository is built to be a global resource for public data and data-backed publication.
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OpARA (Open Access Repository and Archive) is the repository for digital research data of the TU Dresden (TUD) and the TU Bergakademie Freiberg (TUBAF). It offers researchers the possibility of archiving their digital research data and optionally making it accessible to third parties under an Open Access license.
LSHTM Data Compass is a curated digital repository of research outputs that have been produced by staff and students at the London School of Hygiene & Tropical Medicine and their collaborators. It is used to share outputs intended for reuse, including: qualitative and quantitative data, software code and scripts, search strategies, and data collection tools.
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The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
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The IOWDB was designed for the particular requirements of the Leibniz Institute for Baltic Sea Research. It is aimed at the management of historical and recent measurement of the IOW (to some extend of other data, too) and to provide them in a user-friendly way via the research tool ODIN (Oceanographic Database research with Interactive Navigation).
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The Research Data Center for Higher Education Research and Science Studies (FDZ-DZHW) at the German Centre for Higher Education Research and Science Studies (DZHW) in Hannover provides the scientific community with quantitative and qualitative research data from the field of higher education and science studies for research and teaching purposes. The data pool of the Research Data Centre is based on two sources: Firstly, it contains the current surveys of the panels conducted in-house (especially DZHW Graduate Panel, Social Survey, DZHW Panel Study of School Leavers with a Higher Education Entrance Qualification, DZHW Scientists Survey), which are integrated by default. Secondly, the Research Data Centre constantly processes, documents and integrates inventory data of the DZHW and its prior organisations. External data from the research area is also integrated into the FDZ data pool.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
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The University of Northern British Columbia Dataverse is a research data repository for research data from UNBC researchers. Files are held in a secure environment on Canadian servers. The platform makes it possible for researchers to deposit data, create appropriate metadata, and version documents as they work. Researchers can choose to make content available publicly, to specific individuals, or to keep it locked.
META-SHARE, the open language resource exchange facility, is devoted to the sustainable sharing and dissemination of language resources (LRs) and aims at increasing access to such resources in a global scale. META-SHARE is an open, integrated, secure and interoperable sharing and exchange facility for LRs (datasets and tools) for the Human Language Technologies domain and other applicative domains where language plays a critical role. META-SHARE is implemented in the framework of the META-NET Network of Excellence. It is designed as a network of distributed repositories of LRs, including language data and basic language processing tools (e.g., morphological analysers, PoS taggers, speech recognisers, etc.). Data and tools can be both open and with restricted access rights, free and for-a-fee.
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The BonaRes Repository stores, manage and publishes soil and agricultural research data from research projects, agricultural long-term field experiments and soil profiles which contribute significantly to the analysis of changes of soil and soil functions over the long term. Research data are described by the metadata following the BonaRes Metadata Schema (DOI: 10.20387/bonares-5pgg-8yrp) which combines international recognized standards for the description of geospatial data (INSPIRE Directive) and research data (DataCite 4.0). Metadata includes AGROVOC keywords. Within the BonaRes Repository research data is provided for free reuse under the CC License and can be discovered by advanced text and map search via a number of criteria.
Research data from University of Pretoria. This data repository facilitates data publishing, sharing and collaboration of academic research, allowing UP to manage and in some cases showcase its data to the wider research community. Previously UPSpace (https://repository.up.ac.za/) was used for both datasets and research outputs. Now UP Research Data Repository is dedicated for datasets.
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This repository supports the researchers of the Eötvös Loránd Research Network (elkh.org), and to some extent the Hungarian scientists in general.
The Perovskite Database Project aims at making all perovskite device data, both past and future, available in a form adherent to the FAIR data principles, i.e. findable, accessible, interoperable, and reusable.