How to structure and document research data

A good structure and documentation of research data are essential both for your own work, and also to make sure others will understand and interpret your data correctly. While collecting or generating your data, it might be that you primarily focus on the collecting or generating procedure and think less about how to structure and document the data. Postponing the effort to structure and document your data until later may lead to the loss of important information or even errors in your data set. This may spoil your research and in the worst case, you may need to recollect your data (if this is possible).  

Archiving and sharing your data is mandatory for all data that are suitable for open archiving. Good archiving requires good structure and documentation of the data. This assures that others will understand and may reuse your data correctly, and also that you yourself may return to your data in the future without having to rely on your memory. 

In this webinar we offer advice on how to structure and document research data according to best practice at all stages of the research project, and what aspects you should be especially aware of when archiving them. 

For more information about research data management at UiT, see the UiT Research Data Portal. 

The webinar is hosted by Leif Longva and Kathleen Alexandra Smart. 

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