> For the complete documentation index, see [llms.txt](https://gitbook-docs.coinmetrics.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gitbook-docs.coinmetrics.io/reference-data/datonomy-overview.md). # datonomy Overview ## Overview datonomy is a digital asset classification system created by Coin Metrics, Goldman Sachs, and MSCI. It gives investors a consistent, standardized way to analyze the digital assets ecosystem by assigning each covered asset to a single category based on what the asset and its underlying protocol are primarily used for. Classification follows context of use rather than technical architecture. Assets in the same category are ones that can reasonably be expected to compete with each other or perform similar functions, regardless of whether they use different consensus mechanisms or sit on different chains. The starting point is the primary use the protocol's creators describe, but where that stated intent differs materially from how the market actually perceives and uses the asset, observed usage takes precedence. The result is a common vocabulary for the market. Rather than reasoning about several hundred individual tickers, an investor can reason about a handful of categories with stable definitions, which makes datonomy a foundation for portfolio performance measurement, risk management, reporting, and investment strategy creation. ## How the hierarchy works datonomy has three nested levels. Every covered asset sits in exactly one subsector, and its sector and class follow from the code hierarchy rather than being assigned separately. | Level | Code width | What it describes | | --------- | ---------- | --------------------------------------------------- | | Class | 2 digits | The asset's fundamental purpose. | | Sector | 4 digits | The asset's focus area within its class. | | Subsector | 6 digits | The asset's specific product, service, or function. | Codes are positional, so an asset's full ancestry can be read straight off its six-digit subsector code. Bitcoin, for example, is classified as follows. | Level | Code | Name | | --------- | -------- | -------------------- | | Class | `10` | Digital Currencies | | Sector | `1010` | Value Transfer Coins | | Subsector | `101010` | Value Transfer Coins | Where a sector has not been subdivided, it holds a single subsector representing the whole sector and the name repeats at both levels, as it does above. This keeps every asset classified at the same depth. ## Classes, sectors, and subsectors The current taxonomy version defines four classes and 14 sectors, holding 41 subsectors in total. The complete hierarchy is below, grouped by class. Names and codes are reproduced from the live `/taxonomy-metadata/assets` response, which is the authoritative source and the one to query if you need the structure programmatically. For what each category means, see the [methodology](/reference-data/methodologies/datonomy-methodology.md), which defines every class, sector, and subsector. ### 10 Digital Currencies Assets native to blockchains whose primary role is moving value on that blockchain.
SectorSector nameSubsectorSubsector name
1010Value Transfer Coins101010Value Transfer Coins
1020Specialized Coins102010Meme Coins
1020Specialized Coins102020Privacy Coins
1020Specialized Coins102030Remittance Coins
### 20 Blockchain Infrastructure Tokens tied to the protocols and utilities that blockchains are built on and run with.
SectorSector nameSubsectorSubsector name
2010Smart Contract Platforms201010Smart Contract Platforms
2020Blockchain Utilities202010Network Scaling
2020Blockchain Utilities202020Cross-Chain Interoperability
2020Blockchain Utilities202030Blockchain Networks
2030Application Utilities203010Oracles
2030Application Utilities203020Digital Identity
2030Application Utilities203030Governance Tools
2030Application Utilities203040Software Development
### 30 Digital Asset Applications Tokens native to on-chain applications that deliver a specific product or service.
SectorSector nameSubsectorSubsector name
3010Decentralized Finance301010Decentralized Exchanges
3010Decentralized Finance301020Derivatives Trading
3010Decentralized Finance301030Decentralized Lending
3010Decentralized Finance301040Stablecoin Issuers
3010Decentralized Finance301050Prediction Markets
3010Decentralized Finance301060Asset Management
3010Decentralized Finance301070Crowd Funding
3010Decentralized Finance301080Insurance
3020Intermediated Finance302010Intermediated Lending
3020Intermediated Finance302020Payment Platforms
3020Intermediated Finance302030Private Exchanges
3030Business Services303010Professional Services
3030Business Services303020Enterprise Solutions
3040Information Technology304010Data Services
3040Information Technology304020Compute and Private Storage
3040Information Technology304030Wallets and Messaging
3040Information Technology304040Internet of Things
3050Metaverse305010Virtual Worlds
3050Metaverse305020Gaming
3050Metaverse305030NFT Ecosystems
3060Media Services306010Advertising
3060Media Services306020Content and Streaming
### 40 On-Chain Derivatives Tokens whose value derives from another asset, held on or off chain.
SectorSector nameSubsectorSubsector name
4010Stablecoins401010Fiat-backed Stablecoins
4010Stablecoins401020Crypto-backed Stablecoins
4010Stablecoins401030Algorithmic Stablecoins
4020Tokenized Assets402010Asset-Backed Tokens
4020Tokenized Assets402020Synthetic Tokens
4030Claim Tokens403010Liquidity Pool Tokens
4030Claim Tokens403020Staked Tokens
{% hint style="info" %} **This structure is versioned.** The tables above reflect the current taxonomy version. Query [Asset Taxonomy Metadata](/reference-data/datonomy-overview/asset-taxonomy-metadata.md) to get the hierarchy for any version, including historical ones, rather than hard-coding it. {% endhint %} ## Asset coverage To be eligible for classification, an asset must be widely available to investors globally rather than confined to a single venue. Eligibility is measured against a screened universe of digital asset exchanges, and the entry and exit bars deliberately differ: * **To enter,** an asset must have traded at least once in the past 30 days on at least 25% of eligible exchanges. * **To remain classified,** an already classified asset must have traded at least once in the past 30 days on at least 10% of eligible exchanges, subject to a floor of two exchanges. The gap between the two thresholds is intentional. It stops assets near the boundary from entering and leaving the taxonomy on small changes in venue coverage. Assets that fall below the lower bar are reviewed for removal rather than dropped automatically. The classified universe is served by the API rather than published as a static list. Querying [Asset Taxonomy](/reference-data/datonomy-overview/asset-taxonomy.md) with no filters returns every asset currently classified. See the [methodology](/reference-data/methodologies/datonomy-methodology.md) for the full set of guiding principles behind inclusion and classification. ## Governance MSCI administers datonomy. It owns the classification methodology and is responsible for reviewing and approving both the initial classifications and every subsequent change. Coin Metrics contributes the underlying market data, including the exchange screening that determines which venues count toward the eligibility thresholds above, and serves the resulting classifications through this API. An advisory board that may be co-chaired by Goldman Sachs, Coin Metrics, and MSCI provides industry input. Classification changes have no fixed calendar. New assets, reclassifications, and removals are reviewed and implemented as needed, so an asset can be added or move categories at any time. The structure itself is reviewed at least annually, and material changes to it go through a public consultation before they take effect. In practice this means the classification of a given asset is stable most of the time, but you should not assume a fixed effective date for changes. ## Versioning datonomy is versioned, and the API preserves history at two levels. A taxonomy version fixes the set of classes, sectors, and subsectors, each with an effective start and end time. Within a version, each asset's classification is stored as a dated revision, so an asset that is reclassified keeps its earlier classification with the window over which it applied. Both endpoints accept a `version` parameter, and passing `version=*` returns the full history. This is what makes point-in-time analysis possible: a backtest can reconstruct which assets sat in which category on a given date, rather than inheriting today's classification and picking up look-ahead bias. ## API Endpoints datonomy is served by two endpoints. One returns the classification of each asset, the other returns the structure those classifications refer to. {% content-ref url="/pages/wczzCKLsFFtLujz0u3in" %} [Asset Taxonomy](/reference-data/datonomy-overview/asset-taxonomy.md) {% endcontent-ref %} {% content-ref url="/pages/LZ8OrXiyzZsCQJSCeIGd" %} [Asset Taxonomy Metadata](/reference-data/datonomy-overview/asset-taxonomy-metadata.md) {% endcontent-ref %} ## Related * [Asset Taxonomy](/reference-data/datonomy-overview/asset-taxonomy.md): the classification of each covered asset, at `/taxonomy/assets`. * [Asset Taxonomy Metadata](/reference-data/datonomy-overview/asset-taxonomy-metadata.md): the full class, sector, and subsector structure, at `/taxonomy-metadata/assets`. * [datonomy Methodology](/reference-data/methodologies/datonomy-methodology.md): the published classification methodology. * [Asset Profiles](/reference-data/profiles-overview/asset-profiles.md): descriptive reference data for the same assets. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://gitbook-docs.coinmetrics.io/reference-data/datonomy-overview.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.