Enter the Carleton University Dataverse Collection Here

Storage and Repository Decision Chart

Key Benefits | Is the Carleton University Dataverse Collection Right For Me? | When not to use Dataverse | Additional benefits of Dataverse

Borealis, The Canadian Dataverse Repository is a research data platform and repository for sharing, discovering and preserving research data, offered to Carleton faculty and scholars in partnership with the service of the Ontario Council of University Libraries (OCUL). The Carleton University Dataverse Collection is a part of the larger Borealis service.

Borealis/CU Dataverse Collection Repository Structure:

Borealis Repository Structure
Attribution: https://borealisdata.ca/about/

Key Benefits:

  • Robust Canadian storage network: Ontario-hosted with long-term access and preservation in mind
  • Secure data management and access control: easy to use Creative Commons license templates or customizable terms of use and access restrictions supported. It also tracks changes, provides file version control, and creates a backup copy for safekeeping. Support for restricted file access and file embargoes
  • Meets open access and dissemination requirements: for research funders (e.g., Tri-Agency Research Data Management Policy)
  • Recognition and increased visibility: share your data with a global research community (our Dataverse Collection is now indexed in the Federated Research Data Repository (FRDR), Google Dataset Search, Web of Sciences' Data Citation Index, among others)
  • DOIs and citation standards support: rich metadata fields and Digital Object Identifiers (DOI) allow for maximum discoverability for your dataset
  • Customization: Enables such things as creating customized terms of use for your research data and tracking data usage through downloadable metrics and customized guest books
  • Private URLS: Provides the ability to populate private URLs for blind peer reviewing. Anyone you send the URL to will not be required to log into Dataverse to view or download the files

Is the Carleton University Dataverse Collection Right For Me?

When not to use Dataverse:

There are a few instances when the Carleton University Data Collection will not be suitable for use:

  • Large data. Dataverse may not be suitable for large data. It has an individual file upload limit of 3 gigabytes, and a zip file can currently contain a maximum of 1000 files. An alternative option is the Federated Research Data Repository (FRDR) a national data repository that does not limit file sizes.
  • Sensitive data. Dataverse does NOT accept content that contains confidential or sensitive information. Dataverse can be used to share de-identified and non-confidential data only, but it is the sole responsibility of the depositors to remove, replace, or redact such information from datasets prior to deposit into Dataverse. All data deposited into the Carleton University Dataverse Collection must be non-restricted data and cannot contain any private, confidential, or other legally protected information (e.g., personal identifiable information).
  • Streaming audiovisual files. Files in Dataverse generally need to be downloaded to be viewed, and Dataverse does not support streaming; audiovisual files must be downloaded to be viewed.
  • Dataverse is not a subject or domain specific repository. Funders or publishers may require you to house your data in a subject or domain repository. Discover a repository suited to your discipline at https://www.re3data.org/

Source: https://libguides.brandonu.ca/c.php?g=722307&p=5179271

Additional benefits of Dataverse:

Data deposited into the Carleton University Dataverse Collection can be customized or embedded into the researcher’s website with our Theme + Widgets feature. In this way, researchers can make their datasets even more discoverable to their research community and beyond. Widgets are available at the Dataverse and Dataset level and can be embedded in any website to help others find a scholar's datasets more easily.

By increasing research data's visibility using the CU Dataverse Collection, researchers can get recognition and proper academic credit for their scholarly work through a data citation. These citations also help ensure that when research data is published, funder and publisher requirements are met, and data is reused by other scholars, replicated for verification, and tracked to measure usage and impact over time. All of these factors can help fund future research.

Dataverse standardizes the citation of datasets to make it easier for researchers to publish their data and get credit as well as recognition for their work. When you create a dataset in Dataverse, the citation is generated and presented automatically. As an open source framework and research data repository, Borealis: The Canadian Dataverse Repository is committed to helping researchers, journals, and organizations make data accessible, reusable, and open (when possible).

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