# PSDLA

Data licensing has become increasingly important in the age of AI. Whether protecting valuable IP or structuring exclusive deals, there is a need for clear and modular data licensing standards for both data owners and acquirers. The Portex Standard Data License Agreement (PSDLA) framework addresses this.

Inspired by Creative Commons' "pick-a-badge" simplicity, PSDLA lets experts choose a license that matches their commercial goals without re-drafting a full contract each time.

{% embed url="<https://github.com/portex-ai/PSDLA>" %}

## Why use PSDLA?

* Purpose-built for data and AI: clauses cover model-training rights, derivative-model IP, output indemnification, and more.
* Modular: all versions share a common template covering ethical, practical, and transaction considerations, with pre-built clauses for common permutations (e.g., exclusive vs. non-exclusive).
* Human-readable and machine-readable: each license ships as Markdown and JSON for UI integration and API access.
* Versioned: follows SemVer (e.g., `v1.0`, `v1.1`, `v2.0`) to account for improvements.

## PSDLA Overview (v1.0)

| Code                                   | Exclusivity                                                            | Commercial Scope                                                                               | Extra Options                                          | Typical Use Case                                                 |
| -------------------------------------- | ---------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------- | ------------------------------------------------------ | ---------------------------------------------------------------- |
| PSDLA-NE "Non-Exclusive"               | Seller may re-sell at any time                                         | Unlimited commercial use of insights and model outputs; may deploy in production               | Standard AI use-case provisions                        | Datasets that can be sold to many buyers                         |
| PSDLA-EX "Exclusive"                   | Sole buyer for the Exclusivity Term; right of first refusal afterwards | Same freedoms as PSDLA-NE                                                                      | Standard AI use-case provisions                        | Buyer pays premium for a head-start                              |
| PSDLA-NE-L "Non-Exclusive Limited"     | Seller may re-sell under specified limitations                         | Commercial use with seller-imposed limitations                                                 | Seller specifies usage restrictions                    | Seller restricts usage based on ethical or commercial framework  |
| PSDLA-EX-L "Exclusive + Field-Limited" | Same exclusivity as PSDLA-EX under specified limitations               | Commercial use with seller-imposed limitations                                                 | Seller specifies usage restrictions; duration selector | Seller grants exclusivity in one vertical while retaining others |
| PSDLA-RS "Revenue-Share"               | Specified by seller                                                    | Commercial use allowed, but buyer remits Y% of gross revenue from products trained on the data | Audit and reporting clause; duration selector          | Sellers seeking recurring upside from high-value datasets        |

## Configuring a License on the Datalab

When creating a listing, click "Configure License" to open the license editor. You can:

1. Select a base PSDLA variant
2. Set the license duration (1-10 years)
3. Add custom clauses (e.g., field-of-use limitations, specific industry restrictions)
4. Preview the compiled license text

Changes apply only to the listing being edited. The live preview updates as you make changes.

## Contributing

Pull requests welcome. Please open an issue first to discuss major changes or new license permutations. When contributing a new version:

1. Copy an existing license file.
2. Bump the minor or major version as appropriate (`v1.1`, `v2.0`, ...).
3. Update the change-log in the file header.
4. Submit a PR with a clear description of why the change is required.