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Best Practices for Research Data Management - Using Dataverse for Research Data
In Canada, as in many developed countries, requirements for data management are being established across a wide range of scholarly disciplines. In this presentation, Eugene Barsky from the University of British Columbia's ARC Team will offer UBC Library expertise in managing thousands of data files with Dataverse software.
UBC Abacus Dataverse (http://dvn.library.ubc.ca/dvn/) is open-source software, developed by Harvard, which allows researchers to share, cite, preserve, discover, and analyze research data. Dataverse is designed as a self-serve platform, where individual researchers, research teams, and institutes can create their own account and deposit their own data. Dataverse has proven to be a flexible platform that can support many models for research data management services. It offers a range of features that improve data discoverability and access. It also does a good job of managing data files from a preservation perspective: it manages versions, conducts checksums to maintain data integrity, and supports persistent identifiers.
In this session we will cover how to:
- Create and change records
- Metadata, types of metadata, standards
- Uploading files, large files, zipping
- Version control
- Tabular analysis in your browser
- Granular access to datasets: public, institutional, groups
- UNFs for data analysis
- OAI for discoverability
Prerequisite Knowledge and Requirements:
- No previous knowledge or experience required.
Who Should Attend:
- Any researcher interested in best practices for research data management is welcome to attend.
- This session is open to all faculty, students and staff in any discipline.
For more information on this session or the pre-requisites required, please contact us.