Love Data Week, now with a Prequel: Love Methods Week

Research Partnerships wishes you the best this Love Data Week, February 12-16! 

We love data every day of the year, but to celebrate International Love Data Week, we are offering some workshops to help people from every discipline show their data and research outputs some care and affection. Here at UNL, you can learn how to write an NIH Data Management and Sharing Plan, get some tips for humanists in managing their digital (and analog) data, or take a crash course in research data management. But there’s also a listing of events on the official International Love Data Week Website, and many of them are online and open to the public. 

This year, for the first year, some folks are paying attention to the role of methods in making data FAIR (Findable, Accessible, Interoperable, and Reusable), with the inaugural Love Methods Week. This approach makes a lot of sense to me because, as I’ve often said, data don’t stand on their own. They are always observations of something or evidence for a claim. To understand the context in which anything counts as data, we must know how that data was produced.  

But since we’re a little bit late to the game this year (Love Methods Week was January 29-February 2), it might be worth checking out the Love Methods Week web page to see the kinds of training and events the sponsors put on this year. This is also the perfect opportunity to mention Protocols.io, where you can find published research protocols, share your own, and get a DOI to make it easy to cite. We will be talking about some of these things in our upcoming workshops, and please feel encouraged to reach out to talk about making your research workflow transparent and reproducible. 

There are many ways to love your data, including ensuring you keep good documentation and metadata about your data, but whenever I mention the FAIR principles, I talk about the CARE principles in the same breath. The CARE Principles relate to the rights of Indigenous people over data by and about them: they ensure Collective benefit, Authority to control, Responsibility, and Ethics. This is a good reminder that other people want to love and take care of data, too, and that it is our obligation as researchers to make sure we keep everyone who is part of our research involved in the stewardship of the data we produced together to keep our commitments to proper data handling.