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Found 14 result(s)
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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.
York University Libraries makes available Borealis for despositing data . Borealis is a an instance of Dataverse hosted by The Ontario Council of University Libraries, of which York University Libraries is a member.
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Technology has allowed Concordia to collect large amounts of data and information on a variety of topics, which the university feels should be accessible to all. Concordia’s open data makes machine-readable data easy to access from a single point and free to reuse without copyright, patents or other restrictions.
UM Dataverse is part of the Dataverse Project conceived of by Harvard University. It is an open source repository to assist researchers in the creation, management and dissemination of their research data. UM Dataverse allows for the creation of multiple collaborative environments containing datasets, metadata and digital objects. UM Dataverse provides formal scholarly data citations and can help with data requirements from publishers and funders.
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Research Data Centres offer a secure access to detailed microdata from Statistics Canada's surveys, and to Canadian censuses' data, as well as to an increasing number of administrative data sets. The search engine was designed to help you find out more easily which dataset among all the surveys available in the RDCs best suits your research needs.
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<<<!!!<<< Genome data generated by BC Genome Sciences Centre is no longer available through this site as it is regularly deposited into controlled data repositories such as the European Genome Phenome Archive (EGA); ICGC (International Cancer Genome Consortium) and the Genome Data Commons (GDC) >>>!!!>>> Mapping, copy number analysis, sequence and gene expression data generated by the High Resolution Analysis of Follicular Lymphoma Genomes project. The data will be available for 24 patients with follicular lymphoma. All data will be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data.The data from this project will be submitted to public genomic data sources. These sources will be listed on this web site as the data becomes available in these external data sources.
Queen's University Dataverse is the institutional open access research data repository for Queen's University, featuring Queen's University Biological Station (QUBS) which includes research related to ecology, evolution, resource management and conservation, GIS, climate data, and environmental science.
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Agri-environmental Research Data collection is part of the University of Guelph Research Data Repositories (University of Guelph Dataverse). The purpose of this collection is to provide access to, and long-term stewardship of, agricultural and environmental data created at or in cooperation with the University of Guelph.
Biological collections are replete with taxonomic, geographic, temporal, numerical, and historical information. This information is crucial for understanding and properly managing biodiversity and ecosystems, but is often difficult to access. Canadensys, operated from the Université de Montréal Biodiversity Centre, is a Canada-wide effort to unlock the biodiversity information held in biological collections.
The University of Toronto Dataverse is a research data repository for our faculty, students, and staff. Files are held in a secure environment on Canadian servers. Researchers can choose to make content available publicly, to specific individuals, or to restrict access.
Data deposit is supported for University of Ottawa faculty, students, and affiliated researchers. The repository is multidisciplinary and hosted on Canadian servers. It includes features such as permanent links (DOIs) which encourage citation of your dataset and help you set terms for access and reuse of your data. uOttawa Dataverse is currently optimal for small to medium datasets.