Web3Go: On-chain Data Analysis for Polkadot Ecosystem
A large amount of data is generated on the blockchain every day, including transaction data (such as sender and receiver addresses, transaction amount, address balance), block data (such as timestamps, block producers, block rewards), smart contract code ( such as contract logic and contract address), etc.
In the public chains, these data are open to all, and if these data can be reasonably mined and utilized, great value can be generated. However, for non-professional users, it is not realistic to directly obtain and analyze massive on-chain raw data. Fortunately, there are already many on-chain data analysis products that provide various services.
The following are some of the more popular on-chain data analysis products:
However, most of the above data analysis products only support Bitcoin, Ethereum and some EVM chains (such as BSC, Polygon, Avalanche, etc.) and their on-chain applications, and very few support the Polkadot ecosystem. Even if there is support, it is limited to Moonriver and Moonbeam, the two EVM chains of the Polkadot ecosystem.
This may be because Polkadot and Ethereum are very different. Polkadot adopts the architecture of “relaychain + parachains”. Each parachain is a heterogeneous chain that is specialized in different directions, and can define its own Event and Call. In addition, Polkadot has parachain auction, NPoS consensus, and native NFT standard, etc. These differences prevent many data analysis experiences on Ethereum from being directly applied to the Polkadot ecosystem.
However, the data value of the Polkadot ecosystem actually has huge potential. Currently, Polkadot has 13 parachains and Kusama has 27 parachains. Let’s take two parachains as an example. Subscan data shows that as of the time of publication, the Polkadot parachain Acala has issued 642,351 blocks, and a total of 510,548 extrinsic and 924,235 transfers have occurred; Moonbeam has issued 655,274 blocks, a total of 52,541 extrinsics and 1705756 transfer have occurred. In the future, with the launch of more parachains, the business growth of the parachain itself and the increase of applications deployed on the parachain, more data will be generated in the Polkadot ecosystem.
We need to have data products that truly understand and take root in Polkadot ecosystem to make use of these data and provide valuable reference information for developers, media and investors, so as to promote the further development of the ecosystem.
At present, a number of on-chain data products have emerged in the Polkadot community. For example, SubQuery provides developers with data query services of the Substrate-based chain which can be applied to their projects; Subscan provides a multi-chain browser of the Polkadot ecosystem, making it convenient for users to query and index block information; doTreasury provides visualization of Polkadot and Kusama Treasury revenue and expenditure data.
Today we are going to experience a data analysis platform that ordinary users can quickly get started with — Web3Go.
Web3Go (https://web3go.xyz) is an open data analysis platform initiated and incubated by Litentry. It provides easy-to-use yet powerful tools that allow users to query, visualize, and analyze on-chain data.
Web3Go provides a range of data services such as asset trading, micro-analysis and visualization of parachain slot auctions and DeFi activities, and can also create Web3 profiles based on users’ cross-chain behavior data.
Let’s experience Web3Go together.
1. Dashboards
There are many interesting dashboards in Web3Go that provide visual aggregated information for different projects. This time I mainly experienced some of the feature dashboards.
RMRK NFT Garden Dashboard
RMRK is the first NFT standard in Kusama/Polkadot, and many NFTs in the ecosystem are created based on this standard. According to data from Web3Go, there are currently 6,116 RMRK NFT Collections, and the transaction volume of RMRK NFT has reached 79,170 KSM.
RMRK is a very powerful NFT standard, and as RMRK is upgraded to version 2.0, NFTs can own other child-NFTs and resources. For example, a Kanaria bird NFT can be equipped with “child-NFTs” such as different headgear, handheld items, backgrounds, etc., and can also have multiple “resources” such as regular-looking Kanaria birds and custom artwork.
These capabilities obviously greatly improve the playability and imagination of RMRK NFTs, but along with it, the complexity of the data is also greatly improved. How should NFT holders reasonably price an NFT with many “assets”? How can buyers sort out the nested relationships between various NFTs and find works that really deserve attention from the massive data?
In the Kanaria market and the Singular market, the NFT itself is more displayed, and the data that users can refer to is very limited. The RMRK NFT Garden panel in Web3Go provides more information.
RMRK NFT Garden tracks various activities in the RMRK NFT market in real-time, and the displayed data includes transaction volume, number of transactions, listing price, transaction price, and number of buyers.
Entering the page of an NFT collection, you will see some more detailed data, such as the lowest/highest/average transaction price and listing price and the number of buyers.
Specific to a certain NTF page, we can check the creator and owner of that NFT, where the metadata is stored (such as IPFS), and so on. You can also see all past activity records, such as minting, sending, transactions, etc., and you can further view the blocks related to the activity.
If you want to know the latest minted NFT, you can come to the Mint Master page. The most minted collections in the last 24 hours can be found in “Latest Mints”.
Through the chart in the NFT Graph, we can very intuitively see the “family tree” of an NFT, that is, the child-NFTs and resources it has, thus showing the degree of development of the NFT. Clicking on each child-NFT will also display the NFT’s number, picture and introduction, and some child-NFTs also have multiple resources.
Moonbeam&Moonriver Staking Dashboard
Moonbeam and Moonriver are the parachains of Polkadot and Kusama respectively. The block generation mechanism of both is based on Polkadot’s NPoS (Nominated Proof of Stake) mechanism, so the staking process is very similar to Polkadot staking’s.
The Moonbeam/Moonriver parachain network has two roles: Collator and Delegator. The collator is responsible for collecting parachain blocks, which requires a certain technical background and professional equipment; the delegators can delegate their tokens to the collators to obtain staking rewards.
So as a delegator, how to choose the most suitable collator? The following aspects can be considered:
- The Moonbeam/Moonriver collators you support must be in the top 64 staked to be eligible and able to earn rewards
- You need to be the top 300 delegators of the collector in order to share the rewards
- The reward you get is based on “your staked amount / the collator’s total staked amount”, the larger the ratio, the more reward you may get
Web3Go’s Moonbeam and Moonriver Staking dashboards provide Stakers with a lot of reference data. Stakers can track staking activities in the network, and can simulate different staking models to find the best staking strategy based on the current staking rankings of collators and delegators.
Let’s take the Moonbeam Dashboard as an example.
The top column shows the basic information of the network, including the current round, block number, and how many blocks have passed in this particular round so far (Round is the staking time unit in Moonbeam, and a round is 1800 blocks) .
The ranking of the collators is listed below, and the ranking icon is green to prove that the collators are selected in the current round and participate in the block generation. You can also see the amount of self-stake, delegator stake and total stake amount. Avg Blocks represents how many blocks the collator has produced in each round on average in the past 10 rounds, and Current Blocks represents how many blocks have been produced in the current round. APR is the annualized rate of return for the collator. The bar-line chart shows the earnings of nearly 10 rounds.
The Simulator is also a very useful feature.
We click on a collator’s income simulator, enter the amount you want to stake (for example, 1000 GLMR), and it will immediately estimate the range of rewards you will get, as well as the current ranking of your staking amount. In addition, the simulator will show the collator’s reward record in nearly 10 rounds in detail. When you choose a collator, you can use this function to simulate first.
You can also subscribe to email notifications to monitor the staking status of collators. If the collator you delegated falls out of the active set, or if your staking ranking ranks below the 300th of that collator (both of which will result in the failure to obtain staking rewards), Web3Go will automatically send you a reminder.
Karura CDPs Dashboard
We all know that a CDP (collateralized debt position) can be created on the Karura platform, and kUSD can be generated by over-collateralizing KSM and other collaterals. The level of the collateral rate determines the security of the CDP. When the price of the collateral falls to a certain level, causing the collateral rate to fall below the set range, the collateral will be liquidated.
The top of Web3Go’s Karura CDP Dashboard shows the total number of CDPs and the total amount of Debt in the debt position. All CDPs are listed below, including each CDP’s price, collateral, collateralization rate, and also shows whether the current collateralization rate status is “safe”, “warning” or “danger”.
Click on the details page of a CDP to see the historical data line chart of KSM Price, Mortgage Rate, and Profit. You can also see the investment and proposal of the address and the total profit.
Using this panel helps us understand CDPs across the Karura market. You can also refer to the CDP mortgage rate settings of users with similar amounts.
Polkadot&Kusama Crowdloan Dashboard
If you follow Polkadot and Kusama Crowdloan, you can see the basic information of past and ongoing Crowdloan, including lease, contribution data, crowdloan completion, current status, expiration time, etc. You can also see the comparison data of different batches of auctions.
On the details page of each parachain, you can also see how much each address has contributed, the number of contributions and the top five contributors in contribution amount, as well as the increase in contribution amount during the entire crowdloan period.
2. “Profile”
In addition to various data dashboards, Web3Go also has a “Profile” section, which is like the profile of Web3, displaying on-chain assets and on-chain activities of an address. As long as you enter the address, you can track the address of each chain associated with the address, how many assets on which chains are held, which parachains crowdloan has it participated in and contribution amount, what DeFi activities were carried out, and which NFTs are held, etc.
If the address is authenticated, it can also display the account owner’s name, contact information, social media accounts and other authenticated information. It is conceivable that this part can be further combined with Litentry’s on-chain identity system.
In Web3 Go’s Wiki, it is also mentioned that different addresses will be tagged according to their on-chain behavior. For example, some addresses will be marked as “Whale”, and some will be marked as “Strong Holder”. However, this feature does not seem to be available yet in the current version.
3. “Insights”
In “Insight”, various data insight reports are displayed, each report has a theme, and the data in the report is also updated in real-time. For example, the “Polkadot Account Overview” shows the 7-day active accounts, total accounts and transaction rankings; the “Polkadot Transaction Overview” can see the transaction volume, transaction volume, etc.
At present, all Insights are released by the official Web3Go team, and users should be able to publish their own Insights later.
4. Community
Web3Go also provides a self-service query tool. Users can click the “Create” button in the upper right corner to create a new query. The left side of the creation page lists the available datasets and data tables, and the right side can enter SQL statements to query, and post your own query results and corresponding graphs in one click. This function is already available, and you can also see some data charts created and shared by the community on the homepage.
In the official introduction article of Web3Go, it is mentioned that a community-based data platform will be created in the future. Users can post their data needs, and can also offer a certain amount of reward to motivate data professionals to solve that; data scientists can also publish their data analysis results, gradually build a reputation in the community and monetize their knowledge and insights.
About Web3Go
Despite its recent inception (launched by Litentry in October 2021), Web3Go has received a grant from the Web3 Foundation, won several notable prizes from the Octopus Accelerator, Wanxiang, Moonbeam, and has worked closely with the Subquery team and Moonbeam team to provide various visualization insights.
Web3Go is a data project launched and incubated by Litentry. Web3Go will serve as a Data Analyzer, which is an external node providing identity-related data analysis services for the Litentry Network as specified in our article about Litentry’s three-layer technical architecture. The identity data analysis result provided by Web3Go will be a core component in Litentry’s process to generate an aggregated identity score. For example, an address’s on-chain identity as a Litentry Crowdloan supporter will be aggregated with its other on-chain identity and used to obtain better, various Web3 services.
Website: https://web3go.xyz/#/
Twitter: https://twitter.com/Web3Go
Introductory article:
https://web3go.medium.com/introducing-web3go-fcf5f1880a72
Documentation: https://doc.web3go.xyz/
Summary
Our Web3Go experience tour is here first. After the overall experience, we can see that Web3Go is indeed a data analysis product rooted in the Polkadot ecosystem. In particular, several featured panels have been carefully customized according to the situation of each project, and the user interface and interaction are concise. Easy to use, you can get a lot of practical information from it even without a technical background or data analysis expertise.
Of course, as a new product, Web3Go is not perfect. At present, the number of dashboards is still small, and the products of the Polkadot ecosystem are not fully covered. In addition, the content that users can create and publish is still very simple, the labeling and incentive system has not yet been launched, and there is still a certain distance from the vision of the data community. In the future, when the amount of data in the Polkadot ecosystem explodes, cross-chain interactions increase, and more and more content is created by the community, how to keep up with the pace of ecosystem growth and how to recommend high-quality data content to users will also be a big challenge.
I highly recommend everyone to go to https://web3go.xyz/#/ to experience it for themselves. I believe that it will bring you some surprises and take away some data you never noticed.
