1. Can you briefly describe what your research is about?
In our research, we try to identify tax news and signals about US presidents’ future tax changes. We try to identify this tax news from their speeches.
2. How did you do your research?
We use text analytic methods to try to get something out of it. Our primary data is actually publically available; it is just the speeches made by the presidents.
3. What tools did you use to make your research FAIR?
The team used DataVerseNL, particularly for my research.
4. What UM-services did you use?
We used the Data Stewardship services of Maastricht University Library. Maria Vivas-Romero became the person in charge of following the project, creating the DataVerseNL environment and verifying copyright issues with the data providers in the United States.
5. To what extent were you able to make your research FAIR?
We managed to make a DataVerseNl draft. Together, we looked into the most appropriate vocabulary to draft the meta-data for the project. This meta-data was the one used in the field of Economics and used by the American Economic Journal. See more of the policy promoted by the Journal at https://www.aeaweb.org/journals/data/data-code-policy.
For us, the main challenge was how to make it interoperable and re-usable. Trying to think what other researchers might want to do with it, and what kind of format is the most useful for them. It takes a lot of expertise when it comes to this putting yourself in other people’s shoes.
6. Is your data machine-readable?
Yes, the data in the project are script files created by the researchers. These files are all machine-readable. The last version should be uploaded in DataVerseNL at the end of the PhD project.
7. What lessons have you learnt from the experience?
Making sure that other people can understand your data! How to create meta-data and what terminology to use. We had to understand that some ontologies have certain vocabularies or words that are agreed to be understandable in the field. This was the main challenge, but hopefully, we managed to overcome it.
8. How do you think we can benefit from FAIR research?
By sharing all of it, we hope to encourage other people to look into our methods and replicate our research.
Making sure that other people can do it, that they can access our data and understand it. You do not want all of these to fit your own project only when you have done all this work, and you can share it with others. Therefore, others do not have to do it from square one, then each time it is useful for everyone.
I hope at the end the thinking that wins are: “Today, I did a lot of work, but maybe tomorrow I am going to also benefit from somebody else sharing their work with me”. Creating this community of people who create data that benefits all of us is the main idea.
9. Are your metadata shared in a repository?
As explained before, the meta-data has been put in DataVerseNL. I like to wait for the end of my PhD project when my papers are sent to a publisher for review to publish the data.