Saturday, August 29, 2020

What is wrong with FAIR today.

Image of kevlar that has nothing to do with this blog post,
except that it is Openly licensed. Source: cacyle 2005, GFDL.

In the past year, we have been working in the NanoSafety Cluster on FAIR research output (for our group, via NanoCommons, RiskGONE, NanoSolveIT, collaborating with other projects, such as ACENano and particularly Gov4Nano), analyzing resources, deciding where the next steps are. Of course, in the context of GO FAIR (e.g. via the Chemistry Implementation Network), ELIXIR, RDA, EOSC, etc.

But there seems to be something going wrong. For example, adoption by some Open Science communities making FAIR the highest priority (but formally FAIR != Open; arguably it should be: O'FAIR), but also in the strong positioning of the data steward that will make research data FAIR. I never felt too comfortable, but we're about to submit an article discussing this. I like to stress, this is not about how to interpret the guidance. The original paper defines these pretty well, and the recent interpretations and implementation considerations give a lot of context.

What is wrong with FAIR today is that we are loosing focus. The real aim is reuse of data. Therefore, FAIR data without an Open license is silly. Therefore, data that cannot be found does not help. Therefore, we want clear access, allowing us to explain our Methods sections properly. Therefore, interoperability, because data that cannot be understood (in enough detail) is useless.

On the Data stewardship

So, when EOSC presents essential skills, I find it worrying that data stewardship is separated from research. I vehemently disagree with that separation. Data stewardship is a core activity of doing research and something is seriously wrong if that is left to others. It will be p-hacking discussions for the next 100 years.

On the Open license manager

A second major problem is one important missing skill: an open license manager. For this one, I'm perfectly fine leaving that to specialists. The license, after all, does not effect the research. But not having this explicitly in the diagram violates our Open Science ideas (e.g. inclusiveness, collaboration, etc).

Not having open license as core of Open Science is just development of more paywalled Open Science. Look, there is time and place for closed data, but that it totally irrelevant. Bringing up that argument is a fallacy. (If you are a scholar and disagree, you just created an argument that open license management should be a core task of a researcher.)


  1. I feel Open Data and FAIR Data nicely complement each other. Open data that is not findable is not useful. Also for data for which you need to sign a non-disclosure agreement you need to be able to find it and it is helpful if the data is in a common format.

    To me it sounds helpful if a professional reads my data into a database, which is able to produce many different standard data formats and APIs to make it easier for others to use my data. Just as helpful as a professional helping with Open Data; I found that many of my colleagues do not know the general and field-specific data repositories yet.

    We should not pit these concepts against each other. They both help science.

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