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The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
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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Lingnan Dataverse serves as an institutional research data repository for Lingnan University in Hong Kong. It provides a secure platform for the Lingnan research community to deposit, share, and publish their research datasets, and supports data reuse by the global research community.
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Scholars Portal Dataverse is a secure and publicly searchable Canadian data repository, though researchers who deposit their data here can choose how openly available to make their data, from freely accessible to mediated access to inaccessible. Managed by the Ontario Council of University Libraries (OCUL), Dataverse has contributors and adopters from across Canada. Researchers can use Dataverse to search for secondary data, deposit their own data, store metadata, and visualize and explore data.
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.