Main concepts 🔗

Words in bold are business domain names.

Services have terms written in documents, contractual (Terms of Services, Privacy Policy…) or not (Community Guidelines, Deceased User Policy…), that can change over time. Open Terms Archive enables users rights advocates, regulatory bodies and interested citizens to follow the changes to these terms, to be notified whenever a new version is published, to explore their entire history and to collaborate in analysing them. This free and open-source engine is developed to support these goals.

Collection 🔗

Open Terms Archive is a decentralised system. It aims at enabling any entity to track terms on its own. To that end, the Open Terms Archive engine can be run on any server, thus making it a dedicated instance. An instance tracks terms within a single collection.

A collection is characterised by a scope across dimensions that describe the terms it tracks, such as language, jurisdiction and industry.

Example scope 🔗

The terms tracked in this collection are:

• Of dating services used in Europe.
• In the European Union and Switzerland jurisdictions.
• In English, unless no English version exists, in which case the primary official language of the jurisdiction of incorporation of the service operator will be used.

Federation 🔗

In order to maximise discoverability, collaboration and political power, public collections are federated within a single ecosystem. This makes their data mutually discoverable and enables mutualising effort.

Terms types 🔗

To distinguish between the different terms of a service, each has a type, such as “Terms of Service”, “Privacy Policy”, “Developer Agreement”…

This type matches the topic, but not necessarily the title the service gives to it. Unifying the types enables comparing terms across services.

More information on terms types can be found in the dedicated repository. They are published on NPM under @opentermsarchive/terms-types, enabling standardisation and interoperability beyond the Open Terms Archive engine.

Declarations 🔗

The terms that constitute a collection are defined in simple JSON files called declarations.

A declaration also contains some metadata on the service on which the terms apply.

Here is an example declaration tracking the Privacy Policy of Open Terms Archive:

{
  "name": "Open Terms Archive",
  "documents": {
    "Privacy Policy": {
      "fetch": "https://opentermsarchive.org/en/privacy-policy",
      "select": ".textcontent"
    }
  }
}

Add terms to a collection 🔗

Open Terms Archive acquires terms to deliver an explorable history of changes. This can be done in two ways:

1. For the present and future, by tracking.
2. For the past, by importing from an existing fonds such as ToSBack, the Internet Archive, Common Crawl or any other in-house format.

Tracking terms 🔗

In order to track the changes of terms, the engine records a snapshot of documents that contain them by fetching their web location several times a day. The engine then extracts a version from this snapshot by:

1. Selecting the subset of the document (or documents) that contains the terms (instead of, e.g., navigation menus, footers, cookies banners…).
2. Removing insignificant content, that is residual content in this subset that is not part of the terms (e.g. ads, illustrative pictures, internal navigation links…).
3. Filtering noise that can emerge in the terms by preventing parts that change frequently from triggering false positives for changes (e.g. tracker identifiers in links, relative dates…). The engine can execute custom filters written in JavaScript to that end.

After these steps, if changes are spotted in the resulting terms, a new version is recorded.

Preserving snapshots enables recovering after the fact information potentially lost in the extraction step: if declarations were wrong, they can be maintained and corrected versions can be extracted from the original snapshots.

Importing terms 🔗

Existing fonds can be prepared for easier analysis by unifying their format to the Open Terms Archive dataset format. This unique format enables building interoperable tools, fostering collaboration across reusers.
Such a dataset can be generated from versions alone. If snapshots and declarations can be retrieved from the fonds too, then a full-fledged collection can be created.