The measurement and expression of value is a problem that has fascinated people for a very long time, since it relates to a fundamental human need: to trade objects, labor, and ideas.
To enable trade, the values of all objects, labor, and ideas involved need to be measured in units expressed in a common language understandable to all involved in the trade.
Further, such units—currency or other financial instruments are typical examples—are not just used to measure the value of things involved in a trade, but are also used to represent a proxy for such value in transactions.
Defining and constructing such units of measurement is difficult. It is even harder to get a significant group of people and organizations to recognize such a unit as the basis for measuring the value of things that have a direct impact on their lives and goals.
But when a large enough group of entities does end up agreeing upon such a unit of measurement, something borderline-magical happens: The ability to measure and be proxies for the value of other things makes these units of measurement themselves inherently valuable.
To grasp this intuitively, imagine what the “value” of a dollar bill or a gold coin is. The dollar bill can be used to measure the value of other things, and as a result of that use (or utility), the dollar bill itself becomes valuable. The value of the dollar bill is measured by itself. This fact is so obvious to anyone alive today that it’s easy to overlook the elegance and implications that lie underneath.
At the root of the science of Data Economics is the observation that all possible means of measuring and expressing the value of things (and ideas) can be modeled as packages of data (or information) expressed using a specific language.
Modern fiat currencies are simply units of data representing units of credit held with the issuing government. Hard currency such as a gold coin is a package of data made of physical atoms acting as a proxy for the work done to extract and mint the gold used. Similarly, everything else used to “pay for things”—from cryptocurrency to credit card miles to a loyalty card for a local coffee shop that can be redeemed for a free coffee—consists of uniquely identifiable packages of data.
We pay for things with data all the time. The form and identity of such data is typically designated by a central authority such as the United States Treasury, a credit card company, or a local coffee shop.
Unlike any other period in human civilization, we now have the means of capturing and storing almost everything that affects our lives, work, and goals with precision, ease, and efficiency in the form of digital data. The amount of digital data being captured and generated by an individual with a cell phone simply going about their lives would likely surpass the wildest expectations of someone from even a century ago.
The question at the heart of Data Economics is therefore a somewhat obvious one - How can the digital data that each of us—people and organizations—is generating be used to pay for things? Can digital data, generated from different sources, for different reasons, and “owned” by different people and companies, be used to mint products that measure the value of other things and that can be used as a proxy for that value in transactions in the same way that physical currency has in the past?
The ability to measure and transact economic value using products created from ordinary digital datasets has far-reaching implications across every aspect of human life and our relationship with the world. Understanding these implications and enabling the creation of valuable products from raw digital data is therefore the motivation for the entire discipline of Data Economics.
The materials below are designed to give readers a guided tour into the discipline of Data Economics, starting with the basics before expanding on key concepts. We hope that you enjoy the journey and join us in exploring this fascinating new universe together.