这家创企计划在今年后期推出其平台，今日它宣布获300万美元种子轮融资，投资方包括General Catalyst、Greylock、Pantera Capital和光速创投等。
那么这家公司的解决方案是什么？Dirt Protocol创建了一个数据库，任何人都可以往里面发布信息，但发布信息“就要承担风险”，如果信息不属实那么他们就要缴纳罚金。Dirt Protocol并不是要创建一个单一的、绝对的数据仓库，而是去提供工具，帮助开发人员建立自己的数据库。这些数据库可能会被用于ICO（例如提供ICO团队和投资人的信息、流通代币数量）、在线出版等。
Dirt Protocol has raised $3 million to use blockchain to build a trusted platform for structured data.
The company is creating a protocol known as Dirt for crowdsourcing trusted information, using the secure and transparent decentralized ledger technology behind blockchain. It’s like the “Wikipedia for structured data,” the company said.
The investors include General Catalyst; Greylock; Lightspeed; Pantera Capital; Digital Currency Group; SV Angel; ZhenFund; Fred Ehrsam (cofounder of Coinbase); Elad Gil; Avichal Garg; Linda Xie; and others. The full list includes 15 venture firms and 11 angel investors.
Dirt is a protocol for decentralized information gathering. Its mission is to organize the world’s information and make it freely accessible.
“I have been involved with blockchain projects since 2013. Five years ago, there was just Bitcoin,” said Yin Wu, CEO of Dirt Protocol, in a statement. “Now there is an entire ecosystem with alternative currencies and dApps (decentralized apps). But in this new decentralized world we still rely on centralized sources of truth — Twitter determines who is real and CoinMarketCap determines the price of a cryptocurrency. There needs to be a way to determine what is true and build trust without a centralized arbiter.”
She added, “We are building Dirt to solve this problem. Dirt is a protocol that crowdsources trusted information which rewards honesty and penalizes lying. Without relying on any single curator, Dirt is doing to data what Wikipedia did to the encyclopedia.”
That, of course, means disruption.
Data in the 21st century is like oil in the 20th century — an immensely valuable asset that is critical to the economy. From the stock prices to the weather, we depend on accurate and accessible information for our everyday decisions, the company said.
Unfortunately, data is an asset that most companies hoard. This creates data silos, limits competition, and stifles creativity. Dirt Protocol says that structured data about the world needs to be freely available for new applications and utilities to emerge.
No single company should have a monopoly on information and truth, the company said. When you give all that power to a single entity, there are two big concerns: 1) who gets to decide what information is correct and 2) who gets to access the information.
“The question we ask every day at Dirt is: How can we unlock innovation by building and maintaining databases of information that live in the public domain?” the company said.
Dirt is a protocol for decentralized information gathering that makes it “economically irrational for a lie to persist in the network.” The company describes a set of rules for writing and validating information that uses token staking to incentivize honesty.
Similar to Wikipedia, anyone can contribute information. Dirt introduces greater assurance of accuracy because every contributor needs to stake tokens with their data. If the data is correct, it is shared freely. If the data is false, a moderator in the Dirt network can challenge the entry and earn tokens if the challenge is successful.
For crypto enthusiasts, Dirt may sound similar to the concept of a token curated registry (TCR), but Dirt is not a TCR. Instead, it is a protocol to build TCRs.
Since the protocol is a system that makes it economically irrational for people to lie, Dirt naturally extends to domains where there is an incentive to lie. For example, it could crowdsource the list of authorized resellers for luxury brands. Dirt could crowdsource the air pollution ratings in Beijing or the dollar exchange rate in Venezuela.
Wu previously founded Echo Lockscreen, which she sold to Microsoft in 2013. Rather than tackling any one vertical, Dirt wants to first create a general platform for token-incentivized registries that will work across industries and data types. It hopes to create a scalable way to vet information.