A growing phenomenon is becoming increasingly evident—data is truly becoming an asset. But the problem is, owning data and turning data into money are separated by a huge gap.

How exactly can massive amounts of data generate real revenue? Recently, an economist proposed a very interesting framework. He pointed out that the engine of the digital economy consists of three parts: algorithms, computing power, and data. Among them, data is the source, like a gold mine waiting to be mined. The more it is used, the higher its value; it hardly wears out and can continuously generate new economic value.

It sounds promising, but actually extracting this gold mine requires crossing four hurdles:

**Property Rights Issue**—Who exactly owns this data? Who has the right to use it? Who can profit from it? This is the starting point. Without clear ownership boundaries, everything else is pointless.

**Valuation System**—What is the value of a piece of data? How should a complete dataset be priced? Without a unified evaluation standard, the market will fall into chaos.

**Circulation Mechanism**—How can data be traded smoothly like commodities? Secure, standardized trading channels and platforms are needed to support this.

**Governance Framework**—Who is responsible for regulation? How to find a balance between data commercial use and privacy protection? This is essential for long-term healthy development.

But all these point to a deeper issue—trust. Data is intangible and invisible, with almost zero copying cost. How do you know the trading counterpart truly owns this data? How to ensure the entire transaction process cannot be tampered with? Without a foundation of trust, any market cannot operate effectively. This is also why technologies like blockchain are attracting attention in the field of data trading.