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Found 9 result(s)

PRISM Dataverse

University of Calgary Data Repository

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PRISM Dataverse is the institutional data repository of the University of Calgary, which has its purpose in digital archiving and sharing of research data from researchers. PRISM Dataverse is a data repository hosted through Borealis, a service of the Ontario Council of University Libraries and supported by University of Calgary's Libraries and Cultural Resources. PRISM Dataverse enables scholars to easily deposit data, create data-specific metadata for searchability and publish their datasets.

Research Data Unipd

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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.

ICRISAT Dataverse

International Crops Research Institute for the Semi-Arid Tropics Dataverse Network

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ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.

DaRUS

Data Repository of the University of Stuttgart

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DaRUS, the data repository of the University of Stuttgart, offers a secure location for research data and codes, be it for the administration of own data, for exchange within a research group, for sharing with selected partners or for publishing.

DataverseNO

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DataverseNO 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.

Laurentian University Dataverse

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Laurentian University Dataverse is an institutional research data repository for research data produced at Laurentian University.

Texas Data Repository

TDR

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The Texas Data Repository is a platform for publishing and archiving datasets (and other data products) created by faculty, staff, and students at Texas higher education institutions. The repository is built in an open-source application called Dataverse, developed and used by Harvard University. The repository is hosted by the Texas Digital Library, a consortium of academic libraries in Texas with a proven history of providing shared technology services that support secure, reliable access to digital collections of research and scholarship. For a list of TDL participating institutions, please visit: https://www.tdl.org/members/.

Lingnan Data Repository

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Lingnan Data Repository 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.

Redata

Repositorio de datos abiertos de investigación de Uruguay

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The Research Open Data Repository of Uruguay (Redata) seeks to encourage the publication and reuse of national research data results in any area or discipline. It is a project of the National Agency for Research and Innovation (ANII) of Uruguay and has the following objectives: Facilitate the identification, verification and reuse of research results. Minimize duplication of efforts in data collection. Develop capacities at the national level for data management subject to international standards and best practices. Contribute to the development of infrastructures for open science, in line with international recommendations and trends.