FAIR vs. GDPR: which will win?

Sometimes life isn’t fair. No sooner have data librarians been gifted with a popular buzzword that gets across the importance of making data openly accessible to researchers in a way that resonates with them, than another buzzword enters the ring, threatening to knock out the appeal of open data with a single, forceful punch: GDPR, ladies and gentleman, muscles flexing in the opposite corner, grinning with malice and threatening absurd fines.

GDPR, which doesn’t even have the grace to float off the tongue, has researchers, administrators and librarians alike quaking in their boots. No matter what its essence or purpose is scarcely different from its twelve-year-old predecessor, the Data Protection Directive. No matter that its primary target is the dastardly marketing practices of errant companies tricking the hapless consumer into giving up their personal data to those with whom they do business or for purposes against which they have given freely their consent.

In research, will it matter how ethically conceived information sheets and consent forms have been crafted to reassure participants their data will be put to good use? Will it matter what painstaking measures the project’s statistician will take to anonymise personal data and reduce the risk of disclosure of individuals when data could be merged with other data? Or will the data be locked up with nary a thought to how the key could be retrieved, for the mere hint of a risk that shame and misfortune could fall upon the research institution if caught afoul of the dreaded General Data Protection Regulation?

Will fear conquer the altruism of open data? Or will FAIR, with its library friendly jargon - findable, accessible, interoperable, reusable - with its promise of an open science / open research future that breaks down walls between research agendas and accelerates the pace of human knowledge, win the day at last, perhaps even providing humankind with the kind of breakthrough that could save it from itself and reverse the destructive path it is on - solving the interdisciplinary grand challenges of the day such as climate change, inequality and appropriately harnessing artificial intelligence.