‘The FAIR Cheatsheet helps me to publish my research data in an open way’

FAIR principles are becoming more and more important when sharing research data and research software. To help herself finding her way to FAIR data, science historian and philosopher Susanna Bloem used FAIR Cheatsheets, a new tool for Utrecht University researchers.

It may come as no surprise that Susanna Bloem is a supporter of open science. Alongside her PhD research (Dutch) – on how music can help soften mental suffering (see text box) – she is involved in an ethnographic study on the Utrecht open science movement. Interestingly, it was of importance for that study in particular to consider to what extent the research data could be shared openly.

“My colleague and I held interviews with scientists, but those conversations took place under strict secrecy,’  she says. “Even the list with interview candidates is secret, to protect the persons involved. Among other things, we asked them to reflect critically on the academic world, and to share personal experiences about their careers. Such information is sensitive and, if it gets out on the street, could have consequences for their future careers. At the same time we wanted to make our process transparent to outsiders. But how?’

From the outset, Susanna Bloem and her colleagues were aware that they wanted to share their data in a FAIR way. “I see FAIR data as an important way to relate to society,” she says. “If you show how you get your information, you make a more reliable impression. Because you show how knowledge is produced instead of just saying: ‘this is true’.”

Useful checklist

Where do you start, making your research data FAIR? A colleague told Susanna Bloem of the FAIR Cheatsheets: a new tool that helps scientists find their way to FAIR data or code.

These FAIR Cheatsheets consist of a one-page PDF with a checklist. There are two versions: one to make your data FAIR, and a Cheatsheet to make your code FAIR. For each of the four FAIR principles, several ‘recommendations’ are listed. Under the heading Findability you will read for instance: ‘Provide as much descriptive metadata about your dataset as possible.’ And: ‘Write an abstract that describes both your dataset and the research topic.’ This is how the Cheatsheets help researchers step by step.

Very useful, says Susanna Bloem. “To me the FAIR Cheatsheet was a concrete tool to put our commitment to openness and FAIR data into practice. At the same time this thought process gave my research more depth. I had to start reflecting on which files I actually have, what information they contain, what I can and cannot say, what methods we use and why we make certain choices.”

FAIR does not have be complicated at all, but you do need to help researchers get started

Brief and to the point

The FAIR Cheatsheets have been developed by experts from the Utrecht University Open Science Programme and RDM Support (see text box) in consultation with researchers from several faculties. “Researchers don’t always know what to do with FAIR,” explains Jonathan de Bruin, project manager of FAIR Data and Software. “The term focuses mainly on properly setting up the infrastructure of data repositories and that is why it is described with all kinds of abstract, technical terms. Even for an expert like me they are sometimes difficult to understand.’

That is why Jonathan de Bruin and his colleague Jacques Flores wanted to give researchers more tools. “FAIR does not  have to be complicated at all, but you do need to help researchers get started. We can’t expect from staff that they are able to use such a complicated paper about FAIR data themselves. This is how the idea was born to summarise the most important information on one A4 sheet.”

The checklist on the FAIR Cheatsheet is deliberately brief and to the point. “From experience we know that scientists are most helped by this,” says Jonathan de Bruin. “People just wanted to know what they can do. So no endless descriptions, but practical and clear ‘to-do’ items. And we will keep improving the Cheatsheets based on the feedback we get from researchers.”

More help

Some scientists will find the FAIR Cheatsheet almost self-explanatory, according to Jonathan De Bruin, while others may need a bit more help. “Fortunately, Utrecht University can offer that kind of support. As a researcher you can turn to a whole team of data management experts who are happy to share their ideas and are ready to answer your questions. Are you stuck? Send us an email!”

Susanna Bloem also had some additional questions when using the FAIR Cheatsheet. “When is it FAIR enough? Which risks do you run when you make certain parts of your research public? On my own I could not quite figure it out. So I was very glad with the help I got from Angie, Laura and the other specialists.”

Different research domains each have their own jargon, emphasizes Susanna Bloem, and that results in some misunderstandings. “Some words on the FAIR Cheatsheet were really ‘data language’, I could not understand them very well. So you will have to have some discussions, because only in this way you will discover that you have more in common than you think. Where a data expert talks about ‘research domain’ as a Humanities scholar I tend to say ‘academic culture’.  But actually we pretty much mean the same thing.”

Working with the FAIR Cheatsheet gave my research more depth

Meaningful sharing

The sparring with data management experts calls Susanna Bloem an extra benefit of working with the FAIR Cheatsheets. “Together we had good and interesting discussions that also helped to take my research further. Particularly, if you conduct historical or sociological research, you are constantly confronted with the fact that you select data and categorise data yourself. By definition, your research is not objective, and your data, and its interpretation, not neutral. The challenge is to make visible that you work on the basis of sound methods.”

Thanks to the FAIR Cheatsheets Susanna Bloem got a clear insight into what she and her colleagues still had to do in the field of data management, how to do it and the best way to do it. “As a researcher you collect so much information! The FAIR principles help to check what data is relevant to share. After all, it is not about just making all our data public. It is more important to do so in a meaningful way.”

Better research

That ‘meaningful sharing’ is exactly what Susanna Bloem and her colleagues ended up doing in their research.  ‘Our interviews will be kept secret, but we did make the process transparent by recording a reflection after each conversation: a short audio recording in which we look back on the interview and talk about what it has brought us.”

What would Susanna Bloem like to say to colleagues who have little experience yet with FAIR data? “Use these Cheatsheets! FAIR really helps to organize your data. Not just nice for others, but especially for  yourself. It just makes your research better and your work more meaningful.”