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The Future of Crypto Relies on Trusted, Open Data Standards

As institutional players enter the crypto space, they're ready to pay a premium to ensure the data they rely on is both accurate and has strong provenance. But the current landscape of crypto data is fragmented and inconsistent, with different platforms using their own taxonomies and lenses to classify assets and projects. This lack of standardization is hindering adoption by making it harder for users to discover and understand the ecosystem. In this article, we'll dive into the problems with existing data standards, propose a way forward, and invite the community to collaborate on building a unified data layer for crypto.

TLDR:

Crypto data standards are a mess, with platforms using inconsistent tags and data structures to categorize projects, products and assets
Existing standards focus on asset classification, leading to inaccurate labeling and a poor user experience
The Grid is working on an open-source standard that distinguishes assets, products, and entities, enabling better discoverability and understanding
By creating a unified data layer, we can make crypto more accessible and trustworthy for mainstream adoption

The State of Crypto Data Today:

To illustrate the issue, let's look at how different platforms categorize Uniswap, one of the most prominent projects in the space. To help, we introduce the concept of a Lens. This is what area of the project the data is talking about. Is it the Project, Product, Asset or Company.
View of Project Tag Research - Retail platforms
Project
Platform
Main Tag
Other tags
Lens
P_L
Uniswap
8
CoinMarketCap
Decentralized Exchange (DEX) Token
DAO
Yield Farming
Automated Market Maker (AMM)
Decentralized Finance (DeFi)
Asset
Messari
Exchange
Marketplace
Asset
CoinGecko
Decentralised Exchange
Exchange-based Tokens
Decentralized Finance (DeFi)
Governance
Yield Farming
Automated Market Maker (AMM)
Asset
Coinpaprika
DeFi
Exchange
Asset
alchemy
Decentralised Exchange
DeFi Dapps
Product
DeFiLlama
Dexes
Product
TheDappList
DeFi
Exchange
Project
EtherScan
Dex
Asset
Aave
8
CoinMarketCap
DeFi
DAO
Yield Farming
Governance
Lending/Borrowing
Asset
Messari
Lending
Marketplaces
Asset
CoinGecko
Decentralized Finance (DeFi)
Governance
Yield Farming
Lending/Borrowing
Asset
Coinpaprika
DeFi
loans
platform
Marketplace
Asset
alchemy
Decentralized Lending Dapps
DeFi Dapps
Product
TheDappList
DeFi
Lending/Borrowing
Project
DeFiLlama
Lending
Product
EtherScan
DeFi
loans
Asset
As you can see, each platform has its own way of tagging Uniswap, from "Decentralized Exchange" to "DeFi" to "Yield Farming." This inconsistency stems from platforms developing their taxonomies in silos, looking at the ecosystem through different lenses.
Moreover, these tags often fail to capture the true nature of the project. Uniswap is a decentralized exchange protocol, but the UNI token itself is not a DEX—it's a governance token. The protocol, which exists across multiple versions (V1, V2, V3) deployed on different networks (Ethereum, Polygon, Arbitrum), is the actual DEX.
To further complicate matters, the Uniswap ecosystem also includes other products like the Uniswap Wallet, which is managed by Uniswap Labs, the core team behind the protocol. However, Uniswap Labs does not control the protocol itself, which is governed by UNI token holders.
This nuance is lost in the current asset-centric approach to data standards, which often lumps together the token, the product, and the project under a single, catch-all classification. To accurately represent the ecosystem, we need a more granular and multi-dimensional taxonomy that separates these distinct elements and captures their relationships.
In traditional markets, there's a clear distinction between a company, its products, and its assets. For example, the stock $META has an associated company profile that encompasses all of its information, next to the pricing and other data:
CleanShot 2024-01-24 at 16.08.32.png
Image via
This structured reference data, which Wikipedia defines as "data used to classify or categorize other data," provides a controlled vocabulary for looking up and filtering information. However, in the crypto ecosystem, this type of standardized reference data is largely missing, leading to discoverability and usability issues for users trying to navigate the landscape.

The Limitations of Asset-Centric Standards:

Many existing crypto data standards primarily focus on categorizing assets rather than the products and projects behind them. This causes problems like:
Assets getting mislabeled: For instance, the UNI token is often tagged as a "DEX" or "AMM," when it's actually a governance token for the Uniswap protocol. The protocol itself is the DEX/AMM.
Poor user experience: When assets are the primary lens, it doesn't serve users who are looking for products to use rather than assets to buy. An asset-centric taxonomy fails to capture the diversity of projects and use cases in the ecosystem.
When we look at how most people actually use crypto, it's obvious that the current data standards just aren't cutting it. The average user isn't diving into raw blockchain data – they're using apps like wallets, exchanges, and DeFi platforms. And guess what? These apps are often working with inconsistent, siloed data that varies in quality and completeness. It's like trying to navigate a city with a bunch of different maps that don't even use the same street names!
To make matters worse, the existing data standards are dropping the ball when it comes to regulatory info. Users are basically flying blind, not knowing if the projects they're interacting with are compliant or not. That's a recipe for disaster. Sure, some data providers are trying to patch things up by adding more context, like details on a project's team or investors. But it's all piecemeal and lacks the consistency and interoperability that a true industry-wide standard could provide.

The current state of standards within the ecosystem:


View of Classification / Numbering Standards in Web3 Ecosystem
Name of Standard
From who?
Tags
Notes
Link
Full list?
In AIDrive
Written about
In GSHEET
1
Global Crypto Classification Standard (GCCS)
21Shares
CoinGecko
Asset Classifcation
Open
2
DATS: The Digital Asset Taxonomy System
Digital Asset Research
Wilshire
Asset Classifcation
Open
3
DATONOMY™ METHODOLOGY
MSCI Inc
Coin Metrics
Goldman Sachs
Asset Classifcation
Open
4
Bitcoin Suisse Global Crypto Taxonomy (GCT)
Bitcoin Suisse
Asset Classifcation
Open
5
Grayscale Crypto Sectors
Grayscale
Asset Classifcation
Open
6
Digital Asset Classification Standard (DACS)
Coindesk
Asset Classifcation
Open
7
LDACS: Lukka Digital Asset Classification Standard
Lukka
Asset Classifcation
Open
8
Messari Classification System
Messari
Asset Classifcation
Open
9
Digital Token Identifiers Foundation
Etrading Software
Numbering
Open
10
Financial Instrument Global Identifiers (FIGIs)
Kaiko
Bloomberg
Numbering
Open
11
ITSA - International Token Standardization Association (also ITIN)
ITSA
Numbering
Asset Classifcation
Open
12
CFTC
Open
13
CF Benchmarks
Kraken
Asset Classifcation
Open
There are no rows in this table
While these efforts aim to bring structure to the industry, they often conflate asset and product categorization, leading to insufficient and sometimes misleading taxonomies. For example, the GCCS tags "Launch Pad" as an industry under "Decentralized Finance," but a launch pad token is a utility token used within a launch pad product—the two are distinct.
At this point, you might be thinking, "Okay, I get that the current data standards have issues, but what's the solution?" To answer that, we need to take a closer look at two key concepts: reference data and metadata.

What is Reference Data?

Wikipedia defines as "data used to classify or categorize other data." It's typically static or slowly changing over time and provides a controlled vocabulary for looking up and filtering information. Some examples of reference data include:
Corporate codes
structure and constraints
In the context of crypto, reference data could encompass:
Token standards (e.g., ERC-20, ERC-721, BEP-20)
Blockchain platforms (e.g., Ethereum, Bitcoin, Solana)
Consensus mechanisms (e.g., Proof-of-Work, Proof-of-Stake)
Smart contract languages (e.g., Solidity, Rust, Vyper)

Asset/Company Classification:

Classification systems are used to categorize economic activity for accurate reporting and analysis. Governments and organizations worldwide use various systems to ensure consistency in reporting, such as:
NAICS (North American Industry Classification System)
ISIC (International Standard Industrial Classification)
NACE (Statistical Classification of Economic Activities in the European Community)
These systems assign codes to companies based on their primary business activities, enabling the aggregation and comparison of economic data across industries and regions.
In the crypto ecosystem, asset/company classification could involve categorizing projects based on their:
Sector (e.g., DeFi, NFTs, Gaming, Infrastructure)
Use case (e.g., Lending/Borrowing, Stablecoins, Decentralized Exchanges)
Token type (e.g., Governance, Utility, Security)
So, why does all this matter? Well, imagine you're a new user trying to find a DeFi project to start yield farming. You come across a listing on a popular crypto platform, but half the projects are tagged incorrectly, and a quarter of them are no longer even active. Talk about a frustrating experience!
That's where having accurate, standardized reference data and metadata comes in. It's not just about making things easier to find; it's about creating a trusted foundation for the entire ecosystem to build upon.

Metadata: Critical Slow-Moving Data

In addition to classification, there's other essential metadata that needs to be accurately maintained, such as:
Project status: Is the project still active? Inactive projects can lead to a poor user experience if included in listings.
URLs and social media links: These can change over time and need to be kept up to date.
Descriptions: Projects may pivot or evolve, requiring updates to their descriptions across various platforms.
Logos: Ensuring consistent and current project logos can be challenging for marketing teams.
Other important metadata in the crypto space might include:
Contract addresses
Token supply and distribution metrics
Governance processes
Regulatory compliance details
I know this might seem like a lot of technical jargon, but at the end of the day, it all comes down to making crypto more accessible and understandable for everyone. By working together to create open data standards that capture all these different aspects of the ecosystem, we can unlock a whole new wave of adoption and innovation.
So, whether you're a seasoned dev or a curious newcomer, this is something that affects all of us. It's time to build a more transparent, trustworthy, and user-friendly crypto landscape – and it all starts with getting our data house in order.
But hey, don't just take my word for it. If you're passionate about this stuff and want to contribute to the cause, join our community and let's make it happen! [Insert call-to-action and links]

The Path to Better Crypto Data:

At The Grid, we're working on a solution: creating an open-source data standard that distinguishes between assets, products, and entities, and captures granular details at the deployment level. At the most basic level, that may look something like this:
View of Web 2 VS Web 3
Profile
Assets
Products
Entity
1
Meta
$META
Facebook, Instagram, Whatsapp
Meta Platforms INC
2
Uniswap
$UNI
Uniswap X, Uniswap Protocol, Uniswap Wallet
Universal Navigation Inc.
3
Bitcoin
$BTC
Bitcoin Blockchain
There are no rows in this table
This multi-dimensional approach allows for more accurate categorization and enables users to discover projects based on actual use cases and functionality. Imagine being able to easily find all the lending protocols on Ethereum or compare stablecoins across different chains.
Of course, data is only useful if it's trusted. That's why our standard prioritizes data provenance and provides a clear audit trail for how information is sourced and verified. By tying projects to real-world entities and incorporating that into the data, we can create a trusted foundation for the ecosystem to build upon.

The Vision: A Unified Data Layer for Crypto:

Our vision is to create a unified data layer for the crypto ecosystem that becomes a single source of truth for all stakeholders. This open standard would enable:
Better discovery and analysis for retail users trying to navigate the ecosystem
A trusted foundation for institutions and applications to build on top of
Accelerated mainstream adoption by making crypto more accessible and understandable
To get there, we need the community's help. This is an open invitation to projects, platforms, and individuals to get involved and collaborate on building the future of crypto data.
[Call-to-Action with links to community channels and ways to contribute]
Crypto is at an inflection point. As institutional capital flows in and mainstream users start to engage with the ecosystem, the importance of trusted, standardized data has never been higher. By coming together as a community to build an open data standard that captures the complexity and diversity of crypto, we can unlock a new era of growth and adoption.
The future of crypto hinges on trusted data. Let's build it together.
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