Decentralized storage has faced an awkward problem in recent years: most of the stored data just sits there most of the time, with no access, no value flow, and nodes earning no retrieval fees. The overall storage capacity utilization of the network is essentially meaningless. In other words, users spend money to store data, but the data itself remains in a "hibernation" state.

Walrus aims to break this deadlock by leveraging its "programmable" feature. What's the core idea? To enable stored data to be automatically triggered, generating value on-chain through smart contracts.

Here's a real-world scenario: Suppose there is a meteorological dataset stored on Walrus. The data provider can preset a trigger rule—when an on-chain oracle detects that the temperature in a certain area exceeds a set threshold for three consecutive days, the system automatically sends a notification containing data access permissions to the local insurance company, while charging a WAL fee as a "data activation fee." The insurance company needs this data, and after querying, the node earns retrieval rewards. This way, dormant data is transformed from cold storage into an active asset in one go.

Another cooler idea is called "Data Fragmentation Rights." A commercial dataset is split into tens of thousands of encrypted fragments stored across the network, but you don't need to access the original data. Third parties can pay to initiate "distributed computing tasks" on these fragments—such as running a statistical model—where nodes participating in fragment computation and validation earn rewards. The data remains encrypted at all times, but its value is fully extracted.

However, this approach also comes with obvious costs. Walrus is evolving from just a storage network to a "computing edge." Nodes need stronger computational capabilities—not only to store and access data but also to perform verifiable lightweight computations. This presents new challenges for the network architecture, resource allocation, and pricing models. Complex automated trigger logic may also introduce new unpredictability and security risks.

Waking up these dormant data and increasing the network's value density is a path that must be taken. But how to do it—finding the right balance between stimulating network activity and maintaining stability—requires very careful exploration.