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Found 43 result(s)
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
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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Institutional repository intended to gather, preserve and disseminate, through open access, in accordance with the principles of the OAI open archives movement, the documents resulting from the academic, scientific and teaching activity, as well as the institutional publications of the Saint Paul Universities -CEU, Cardenal Herrera-CEU, Abat Oliba CEU and its dependent Academic Centers.
Chapman University Digital Commons is an open access digital repository and publication platform designed to collect, store, index, and provide access to the scholarly and creative output of Chapman University faculty, students, staff, and affiliates. In it are faculty research papers and books, data sets, outstanding student work, audiovisual materials, images, special collections, and more, all created by members of or owned by Chapman University. The datasets are listed in a separate collection.
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
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CURATOR (Chiba University's Repository for Access to Outcomes from Research) captures, preserves and makes publicly available intellectual digital materials from research activities on Chiba University campuses, including peer-reviewed articles, theses, preprints, statistical and experimental data, course materials and softwares. CURATOR is intended to function as the portal for the outcomes from Chiba University's research activities. The University Library is responsible for building and operating CURATOR under the guidance of the Faculty Committee for Improved Scholarly Information Availability, which commissioned by the Library Board of Faculty Representatives to systematically promote and arrange disseminative activities by the University.
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DataDOI is an institutional research data repository managed by University of Tartu Library. DataDOI gathers all fields of research data and stands for encouraging open science and FAIR (Findable, Accessible, Interoperable, Reusable) principles. DataDOI is made for long-term preservation of research data. Each dataset is given a DOI (Digital Object Identifier) through DataCite Estonia Concortium.
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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 Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
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Gambling Research Exchange Ontario (GREO) is a knowledge translation and exchange organization that aims to eliminate harm from gambling. Our goal is to support evidence-informed decision making in responsible gambling policies, standards and practices. In line with this mandate, datasets curated in this archive relate to gambling and reducing gambling related harms.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.
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ISTA Research Explorer is an online digital repository of multi-disciplinary research datasets as well as publications produced at IST Austria, hosted by the Library. ISTA researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researches, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
The Mindboggle-101 data consist of three data sets: (1) individually labeled human brain surfaces and volumes, (2) templates (unlabeled images combining the individual brains, used for registration), and (3) atlases (anatomical labels combining the individual brains, used for labeling).