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Research Data Services

Guidance, tools, and training to support faculty and students working with research data.

About Data Curation

Data Curation is the documentation, description, and management of research data to produce datasets that are FAIR: Findable, Accessible, Interoperable, and Reusable.

It is a process that adds value to research by optimizing data sets for current use and future discovery and reuse. Approaches to data curation will depend on the characteristics of the data being collected (e.g. file-type, size, sensitivity), and the repository where it is being deposited.

When you deposit research data into Dataverse, UVic's Data Curation Librarian will curate and review your dataset in line with compliance to the Dataverse Deposit Guidelines.

Please contact the Data Curation Librarian with any questions. 


Data Curation 101

The Inter-university Consortium for Political and Social Research (ICPSR) quickly explains the intricacies of the work data processors do every day to find and fix issues in the data, ensuring their long-term availability and value to the research community. 


Recommended Resources

  • Dataverse Curation Guide (Portage) 
    This guide provides step-by-step instructions for curating new datasets deposited in Dataverse. The guide is framed around the acronym CURATION to provide an easy reminder for curators, especially those starting out, of the main steps in the curation process.

     
  • DCN Data Primers (GitHub)
    A repository of guides developed by the Data Curation Network (DCN) to support good curation of specific software file types (e.g. netCDF, SPSS, QGIS, MS Excel, Jupyter Notebooks).
     
  • Sharing Code and Data (Cambridge)
    A compilation of various tools and resources that could be useful for transitioning to more open and reproducible science.


  • Curation Workflows (Data Curation Network)
    The US-based Data Curation Network’s Curation Workflow page offers a number of valuable data curation materials, including a description of their CURATED model (with downloadable checklists), and their data curation primers, which provide detailed guidance for curating a wide variety of data types.

 

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