This ERC defines a series of interfaces for the abstraction of storage of on-chain data by implementing the logic functions that govern such data on independent smart contracts. "On-chain Data Containers" (ODCs) refer to the separation and indexing of data storage away from data management. We propose that on-chain data can be abstracted and stored in smart contracts called "Data Objects" (DO), which answer to external data indexing mechanisms named "Data Points" (DP). This data can be accessed and modified by implementing (one or many) separate smart contracts identified as "Data Managers" (DM). We introduce two mechanisms for access management: first, through a "Data Index" (DI) implementation, the "Data Managers" (DM) can be gated from accessing "Data Objects" (DO); second, a "Data Point Registry" (DPR) implementation manages the issuance of "Data Points" (DP). Lastly, we introduce the concept of data portability (horizontal data mobility) between implementations of "Data Index" (DI), enabling massive updates to the logic without affecting the underlying data storage.
As the Ethereum ecosystem grows, so does the demand for on-chain functionalities. The market encourages a desire for broader adoption through more complex systems and there is a constant need for improved efficiency. We have seen times when an explosion of new standard token proposals was solely driven by market hype. While ultimately each standard serves its purpose, most of them require more flexibility to manage interoperability with other standards. A standard adapter mechanism is needed to enhance interoperability by driving the interactions between assets issued under different ERCs.
Without such mechanisms, most projects have implemented bespoke solutions for interoperability. This is an inefficient approach and leads to a fragmented ecosystem. We recognize there is no “one size fits all” solution to solve the standardization and interoperability challenges. Most assets - Fungible, Non-Fungible, Digital Twins, Real-world Assets, DePin, etc - have multiple mechanisms for representing them as on-chain tokens through the use of different standard interfaces and the diversity of standards spurs innovation.
However, for these assets to be exchanged, traded, or otherwise interacted with, protocols must implement compatibility with the relevant interfaces to access and modify on-chain data. This is especially challenging when considering the previously mentioned bespoke solutions for interoperability. Additionally, the immutability of smart contracts complicates the ability of already deployed protocols to adapt to new tokenization standards, which is critical for future-proofing implementations. A collaborative effort must be made to enable interaction between assets tokenized under different standards. The current ERC provides the tools for developing such on-chain adapters.
We aim to abstract the on-chain data handling from the logical implementation, exposing the underlying data independently of the ERC interface. We propose a series of interfaces for storing and accessing data on-chain in contracts called "Data Objects" (DO), grouping the underlying assets as generic "Data Points" (DP) that may be associated with multiple interoperable and even concurrent "Data Manager" (DM) contracts. This proposal is designed to work by coexisting with previous and future token standards, providing a flexible, efficient, and coherent mechanism to manage asset interoperability.
Data Abstraction: We propose a standardized interface for enabling developers to separate the data storage code from the underlying token utility logic, reducing the need for supporting and implementing multiple inherited -and often clashing- interfaces to achieve asset compatibility. The data (and therefore the assets) can be stored independently of the logic that governs such data.
Standard Neutrality: A neutral approach must enable the underlying data of any tokenized asset to transition seamlessly between different token standards. This will significantly improve interoperability among other standards, reducing fragmentation in the landscape. Our proposal aims to separate the storage of data representing an underlying asset from the standard interface used for representing the token.
Consistent Interface: A uniform interface of primitive functions abstracts the data storage from the use case, irrespective of the underlying token's standard or the interface exposing such data. Data and metadata can be stored on-chain, and exposed through the same primitives.
Data Portability: We provide a mechanism for the Horizontal Mobility of data between implementations of this standard, incentivizing the implementation of interoperable solutions and standard adapters.
Data Point: A uniquely identifiable reference to an on-chain data structure stored within one or many Data Objects and managed by one or many Data Managers. Data Points are issued by a Data Point Registry.
Data Object: A Smart Contract implementing the low-level storage management of information indexed through Data Points.
Data Manager: One or many Smart Contracts implementing the high-level logic and end-user interfaces for managing Data Objects.
Data Point Registry: One or many Smart Contracts used for managing the issuance of Data Points. Additionally, a Data Point Registry defines a space of compatible or interoperable Data Points.
Data Index: One or many Smart Contracts used for managing the access of Data Managers to Data Objects.
The keywords "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119 and RFC 8174.
bytes32 storage units.Data Points are a low-level structure abstracting and indexing information. Data Points act as pointers to information stored within data structures in Data Objects. Data Points are allocated by a Data Point Registry. The Data Point SHOULD store which Data Point Registry initialized it within its internal structure. Each Data Point SHOULD have a unique identifier provided by the Data Point Registry when instantiated.
Data Objects are entrusted with the storage and management of data. Data Objects SHOULD implement the logic for managing the storage of on-chain data. Data Object internal data structure SHOULD use Data Points for indexing information.
Data Objects CAN receive read(), write(), or any other custom requests from a Data Manager requesting access to a storage structure indexed by a Data Point.
As such, Data Objects respond to a gating mechanism given by a single Data Index. The function setDIImplementation() SHOULD enable the delegation of the management function to an IDataIndex implementation.
IDataIndex.read() or IDataObject.read() to read data from Data ObjectsIDataIndex.write() to write data to Data ObjectsData Managers are independent smart contracts that implement the business logic or "high-level" data management. They can read() from a Data Object address and write() through a Data Index implementation managing the delegated storage of the Data Points.
The Data Point Registry is a smart contract entrusted with Data Point access control. Data Managers may request the allocation of Data Points to the Data Point Registry.
The Data Index is a smart contract entrusted with access control. It is a gating mechanism for Data Managers to access Data Objects. If a Data Manager intends to access a Data Point (either by read(), write(), or any other method), the Data Index SHOULD be used for validating access to the data.
The mechanism for ID management determines a space of compatibility between implementations.
The decision to encode Data Points as bytes32 data pointers is primarily driven by flexibility and future-proofing. The use bytes32 allows for a wide range of data encodings. This provides the developer with many options to accommodate diverse use cases. Furthermore, as Ethereum and its standards continue to evolve, encoding as bytes32 ensures that the Standard Adapters built with the current ERC can reference future data types or structures without requiring significant changes to the adapter itself. The Data Point encoding should have a prefix so that the Data Object can efficiently identify compatibility issues when accessing the data storage. Additionally, the prefix should be used to find the Data Point Registry and verify admin access to the Data Point. The use of a suffix for identifying the Data Point Registry is also required, for the Data Object to quickly discard badly formed transactions that aim to use a Data Point from an unmatching Data Point Registry.
Data Manager implementations decide which Data Points they will be using. Their allocation is managed through a Data Point Registry, and the write() access to the Data Point is managed by passing through the Data Index implementation.
Data Objects are independent separate Smart Contracts that implement the same read/write interface for communicating with Data Managers. This is a decision mainly driven by the scalability of the system. Offering a simple interface for this layered structure enables different applications to have their addresses for storage of data independently from the asset's interface. It is up to each implementation to manage access to their Data Point storage space. This enables a wide array of complex, dynamic, and interactive use cases to be implemented with multiple ERCs as well as other smart contracts, including the embedding of cross-chain and rollup logic for asset management.
Data Objects offer flexibility in storing mutable on-chain data that can be modified as per the requirements of each specific use case. This enables the Data Managers to hold mutable states in delegated storage and reflect changes over time, providing a dynamic layer to the otherwise static nature of storage through most other standardized interfaces.
Data Managers can decide to migrate the complete storage management of a Data Object from one Data Index implementation to another. As the Data Index implements user ID management, this mechanism enables a Data Manager to upgrade its internal access control mechanisms without affecting the underlying storage of value, as it is located elsewere (in the Data Object). We call this mechanism "Horizontal Data Mobility/Portability".
This ERC is intended to augment the functionality of existing token standards without introducing breaking changes. As such, it does not present any backward compatibility issues. Already deployed tokens under other ERCs can be wrapped and indexed as Data Points and managed by Data Objects, and later exposed through any implementation of Data Managers. All interoperability integrations will require a compatibility analysis, depending on the use case. However, the interfaces defined in this ERC define a framework for adapting one standard to another through storage abstraction.
We present an educational example implementation of a Standard Adapter showcasing two types of tokens (Fungible and Semi-Fungible) with shared data storage. The end user can interact with this implementation through one of two types of interfaces: The semi-fungible one (represented through a single Data Manager), and the fungible interface (represented by many Data Managers). The abstraction of the storage from the logic is achieved through the use of a single Fungible Fractions Data Object. A factory is used for deploying the Fungible token interfaces that share storage with each semi-fungible collection. Note that if a transfer() is called by either interface (Fungible or Semi-Fungible), both interfaces are emitting an event.
This example has not been audited and should not be used in production environments.
See contracts
The access control is separated into three layers:
write operations.A common task for a Data Object is to store user-related data, while the Data Manager implements the logic for managing such data. Both Data Objects and Data Managers often require the management of user IDs. A Data Index can offer logic for user management (i.e. IDs based on address) that are independent of any particular implementation, but care must be taken in selecting these identifiers. If chosen improperly, they could hinder a Data Manager's ability to migrate between different Data Indexes.
No further security considerations are derived specifically from this ERC.
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