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Best Practices for Research Data Management (RDM) : Using Dataverse for Research Data Barsky, Eugene
Description
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 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
Item Metadata
Title |
Best Practices for Research Data Management (RDM) : Using Dataverse for Research Data
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Alternate Title |
WestGrid/Compute Canada Online Workshop
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Creator | |
Date Issued |
2016-11-16
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Description |
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 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
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Subject | |
Genre | |
Type | |
Language |
eng
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Date Available |
2017-01-27
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-ShareAlike 4.0 International
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DOI |
10.14288/1.0340263
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-ShareAlike 4.0 International