Video: Tokenizing real-time data – Streamr explained in 2 minutes

(If you can’t watch the video, find the text below):

Streamr aims to tokenize the value in real-time data.

For example, let’s consider a self-driving electric car. For optimal operation, it constantly needs data from other machines, such as traffic congestion information from other cars, electricity prices on nearby charging stations, weather forecasts, and so on. Streamr provides a single interface for real-time data delivery and payment, making data streams tradeable by people and machines using the cryptographic token called DATAcoin which lives on the blockchain. The car can autonomously get the data it needs and pay for it. In turn, the car can sell the data it produces, such as traffic data to other cars, road condition measurements to a smart city, location and battery level to advertisers, and so on. A data stream economy is born.

Streamr is implemented as a decentralized peer-to-peer network. A data source can connect to any node in the network, publish a data point, and the network will instantly deliver it to valid subscribers. Horizontal scalability is achieved via a clever sharding scheme. The network integrates with the Ethereum blockchain, using smart contracts for security-critical operations like monetization and access control.

Decentralisation means that anyone can run a node in the network and earn DATAcoin in exchange for providing bandwidth to the network. The network is run by its users instead of a big corporation, meaning that YOU own, control, and monetize your data. It also means that the network continues to operate even if a large number of nodes go down due to attack or failure.

In addition to the network itself, we’re creating two applications.

We’ll create a marketplace to make it easier for data buyers and sellers to find each other. It’s kind of like an “app store for data streams”, and it uses a reputation system to showcase the most popular and trustworthy data.

To make it easy for developers to build data-driven decentralized applications, we have a visual programming environment and real-time analytics engine. It’s already up and running, and allows users to seamlessly combine scalable off-chain analytics with on-chain smart contracts.

We make your streams come true.

Thanks for watching! For more information, visit our website. You’re welcome to join our Slack and follow us on Twitter. Read about our collaboration with Golem and other projects in our blog, and of course don’t forget to check out our white paper.

Do-It-Yourself Real-Time Prediction Market With Streamr

What is the most powerful prediction engine in the world? A crystal ball? A deep neural network? The human brain? The collective brainpower of mankind?

The collective wisdom of the crowd (including algorithms too) can produce unbeatable future estimates of asset values, sports outcomes, and presidential elections. Prediction markets attempt to capture this wisdom by creating a mechanism in which probabilities emerge as a result of collective betting. This is similar to how company valuations emerge on the stock market as the result of collective bidding. Both phenomena are based on the efficient-market hypothesis. For an entertaining exploration of the ideas, “The Wisdom of Crowds” by James Surowiecki is very much worth reading.

To realize the relationship between betting and prediction markets, consider a simple betting game with only two possible outcomes: “up” or “down”. Say, you witness a situation where many bets have already been placed, and 90% of the bets are on “up” and only 10% on “down”. Which would you consider the much more likely outcome?

In the blockchain space, projects such as Augur and Gnosis are building decentralized prediction markets based on Ethereum. Inspired by these, we wanted to build a real-time version which leverages our data platform and the visual editor. The demo is based on the streaming real-time ETH/USD price feed from GDAX, an Ethereum smart contract to hold bets and handle payouts, and a Streamr canvas which keeps track of the prediction rounds. It also acts as an oracle, calculating the correct outcome and reporting it to the smart contract.

In the demo, participants can predict ETH/USD price changes 5 minutes into the future. This is a simple game where the binary outcome is either “up” or “down”. Submitting predictions for a round closes 5 minutes before the resolution. To incentivize correct predictions and disincentivize incorrect ones, players place bets in ether to back their predictions. Bets placed on the incorrect outcome are distributed to the winners in proportion of the bets.

Obviously, the distribution of bets will only give meaningful predictions on a market with enough liquidity (players), which our little demo may not have at all times. 🙂

This example works in the Rinkeby testnet. The chart below, embedded from the Streamr canvas, shows the recent ETH/USD price and the outcomes of the most recent 5 min prediction rounds. The demo is live and interactive. Enter your bet in ETH, and press either the “up” or “down” button to lay your (crypto)money down!

In case the betting controls are not visible, your browser is not blockchain-enabled. Try the Metamask plugin for Chrome, or Mist, and get some test ETH from the Rinkeby faucet or by asking someone on our Slack.


The payout logic is coded to this smart contract which is called by the Streamr canvas that calculates the correct outcomes and drives the above chart. An embedded view of the canvas is shown below (open it in full screen or in the editor).

Questions and comments about this post and Streamr in general are appreciated! Join us on Slack, and of course feel free to follow us on Twitter as well.