UDL & builders
The Universal Data License (UDL) (opens in a new tab) provides content creators with a straightforward way to define how their content can be used, along with the prices they set for its use. It is a standardized and parameterized approach that opens up new financial opportunities for creators and builders.
Traditionally, online content sales tied creators to the licensing terms of individual platforms. This meant conforming to multiple different agreements for streaming on platforms, like with Spotify and Apple Music. These platforms are designed to extract the maximum value from creators, leaving them with only a small percentage of revenue, and while major artists might have the power to negotiate better terms, most creators find themselves constrained.
With the UDL, creators can detail exactly how they allow their content to be used. Using the UDL, marketplaces can then identify and autonomously promote content, bypassing manual permissions as the licensee has already granted approval.
NFT ownership is managed by a smart contract, and while the contract clearly calls out who owns which NFT, it does nothing to define what usage rights are granted to each owner. This means each NFT comes with unique rights, and that owners end up having to wade through detailed contracts to understand. For example, purchasing a Bored Apes NFT offers the buyer expansive rights (opens in a new tab), even allowing them to feature the NFT in media productions. Conversely, with Coke's NFT release (opens in a new tab), owning the NFT doesn't authorize you to repurpose the Coke logo for competing ventures.
The Universal Data License (UDL) provides a structured way to clarify these permissions for NFT holders. To add a UDL to an NFT, creators simply need to incorporate UDL-specific tags when uploading NFT metadata.
We also have a tutorial on adding a UDL to NFTs.
The UDL introduces the
Derivation tag, specifically designed to grant the right to create derivative works based on the original content (opens in a new tab). When considering the training of AI models, especially those that generate images, the source data's licensing terms are crucial. AI models ingest and learn from this data, with the quality and diversity of the input data directly influencing the type of images the AI produces.
If an AI is trained on data protected by copyrights that prohibit the creation of derivative works, users run the risk of violating these copyrights when using the AI's outputs. Conversely, training an AI exclusively on data that explicitly permits the creation of derivative works ensures that all images or outputs generated by that AI remain free from potential copyright infringements.
The UDL and Creative Commons (CC) (opens in a new tab) both aim to empower creators by giving them tools to define the terms under which their content can be used. However, a key distinction between them is the parameterized nature of the UDL.
While Creative Commons offers a set of predefined licenses, each with its own fixed terms, the UDL allows creators to define specific usage terms via standardized metadata. This means that with the UDL, creators can customize license terms when they upload content by setting metadata tags (opens in a new tab). In contrast, Creative Commons' static nature requires creators to pick from the available licenses without the ability to customize individual parameters.
Additionally, CC is primarily focused on credit and attribution, it doesn’t define terms for fees or revenue share. UDL is both more customizable than CC and more expansive.
The UDL is a licensing framework, and Digital Rights Management (DRM) is a set of access control technologies that limit the use of digital media or devices after sale. They are two different, but complementary technologies. While UDL defines usage terms via metadata, it doesn't enforce any control of content access. Encryption-based DRM could be used alongside UDL to enforce the terms specified, ensuring both clarity of rights and security of content.
One potential way to manage ownership of UDL assets is with the use of custom tokens. You’d do this by creating a smart contract that creates a new token with a fixed supply. The tokens would be fully tradeable and their ownership would represent ownership of the UDL asset. The smart contract would expose a function that accepts revenue payments and automatically distributes them proportionally based on token ownership.
If you’re interested in learning more, we have a tutorial on building an ERC20 token to manage UDL ownership.
UDL is a set of rules and notably does not include any definition for how those rules are to be enforced. This opens up significant opportunities for builders looking to make an impact in the space.
- Building an NFT platform where users can easily define licensing rules for their creations.
- An AI image generation model trained only on assets that allow derivative works.
- A TikTok-like app that allows users to remix songs that allow derivative works to be created.
- A platform for automatically deploying ERC20 tokens to manage ownership of UDL content.
- A DRM system that uses LitProtocol (opens in a new tab) to encrypt data, and making it available under terms defined by the UDL.
What will you build?