"Why I Chose to Join data.world" — Dean Allemang, Principal Solutions Architect

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During that time, I’ve come to believe that data plays a role beyond good enterprise management; indeed, it holds the key to the survival of the human race.

I believe that good data management on a global scale — e.g., via the FAIR Data Principles — is a prerequisite for unlocking that potential. And while there are a lot of data platforms out there, none of them has the potential to support a vision of a global FAIR data movement as well as data.world.

That’s why I chose to join the company. My personal goal is to make data.world the best FAIR platform in the world, and to make our company the leader in the transformation to a global web of FAIR data.

But how did I get here? And what exactly persuaded me that data.world is best positioned to lead the charge to the FAIR data promised land?



How Do You Go from a Degree in Pure Mathematics to Being a Consultant in the Semantic Web?
I had the good fortune to spend a week in canada whatsapp number data November 2021 visiting one of my alma maters, the University of Cambridge. I made contact with Mark Perkins, a fellow Cambridge alum, who asked me a simple question: "How did you go from doing a degree in Pure Mathematics to being a consultant in the Semantic Web?"

This is an interesting question, and it touches on a lot of key points in my career. After leaving Cambridge in 1984, and realizing that I was not the sort of world-class mathematician that would solve a 400 year-old problem — like some of my colleagues — I moved on to Artificial Intelligence (AI). It is important to understand that in those days the prevailing goal of AI research was to create so-called "Expert Systems.”

The basic idea — in many labs, and certainly in the one I ended up working in — was that there was such a thing called "knowledge,” and that certain people had it, making them experts in their field. If we could just formulate that knowledge in such a way that a computer could process it, then a computer could perform at expert levels. Then we could replace experts with computers.

Not surprisingly, to modern minds anyway, even the occasional system that achieved technical success in these matters failed to catch the interest of the general public. It seemed that nobody really wanted to pay a visit to a computer program when they could instead see a human physician.

Dean Allemang - Data holds the key to the survival of the human race

So we retreated to expert decision support systems; could we represent knowledge in such a way that a trained physician could have access to far more information, at their fingertips, than they could possibly know or keep current with? Such a system could improve the quality of human performance in important areas. Imagine if a physician could have all medical knowledge at their fingertips, even during a consultation! What a powerful idea this could be.

Around 1995, a few things happened to make me become disillusioned with AI. We had entered what was to be known as the "AI Winter" when interest dried up. Funding and new research also became scant, while leaders in the field published embarrassing articles. But most importantly, a new way of looking at information became popular: the World Wide Web.