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Sharing and Archiving Your Data During Remote Work

By WashU Libraries

Data Services recognizes that this is a tough time to progress in your research given that collection and analysis have undoubtedly been impacted by our new normal of remote work. One significant step you could take during this time is reviewing and sharing data from projects that have reached a milestone or have been completed.   

Why Share? 

As you know, if you received federal funding for your project, data sharing is a stipulation of the grant. In addition to this requirement, there are many other reasons for sharing: facilitating citation, furthering your field’s research, and increasing trust in your results. 

Sharing Quality, FAIR Data 

Before shared data is published, it goes through a formal curatorial review. During this process, someone reviews the documentation and data and provides feedback on whether the data meets FAIR principles (meaning that the data are findable, accessible, interoperable, and reusable) and works with the researcher to make necessary improvements. FAIR data are the only data worth sharing.  

Data Services Can Provide Curatorial Review of Your Datasets to Make Your Data FAIR, Which Includes

  • verifying that files open and run 
  • checking that data are complete 
  • ensuring documentation is adequate to support reuse by someone else 
  • confirming the data are shared in a format that is open and interoperable, and where possible transforming it to data to open formats 
  • ingesting into our repository with a DOI and descriptive metadata so colleagues can find it 

Expertise

We have trained experts in house, and we are part of the Data Curation Network, which shares expertise across institutions to meet curation demands. To get the process started go to our guide on submitting data.

Data Services Support for All Core Services 

The Data Services team is working remotely during the COVID-19 crisis and we encourage you to reach out to us for assistance related to our core services:

  • data curation
  • data management
  • data analysis
  • data visualization
  • data literacy
  • geographic information systems (GIS)

You can find more information and our contacts on our website.