Expressions

In any social network, people need to be able to communicate. In ADAM, Agents communicate by creating Expressions using Languages:

const url = await ad4m.expression.create(content, language);

The resulting URL are identified like this: <language>://<expression>.

To ensure authenticity Expressions will be signed by the Agent that created it. Any Agent can then retrieve the expression, get the data and validate the signature:

const expression = await ad4m.expression.get(url);

The content of the expression result will look something like this:

{
    author: "did:key:zQ3shv5VUAbtY5P1jGsPzy7L27FTxeDv2hnhVp9QT3ALNCnQ2",
    timestamp: "2023-06-21T14:47:48.935Z",
    data: "Hello World!",
    language: {
        "address": "literal"
    },
    proof: {
        "valid": true,
        "invalid": false
    }
}

Creating an Expression

We will go into depth on how to use other languages or how to create your own, but for now let's use the simplest language that is included in ADAM – the Literal language. The Literal Language is an AD4M Language without back-end. It stores JavaScript literals (i.e. strings, numbers and objects) by encoding them into the Expression URLs.

const url = await ad4m.expression.create("Hello World!", "literal");

When running create the data will be created using the language, and automatically signed by your agent. The result when creating an expression will be a URL formatted like this <language>://<expression>.

Retrieving an Expression

By using the URL of the expression, you can retrieve it's data:

const expression = await ad4m.expression.get(expressionUrl);

The result will look something like this:

{
  "author": "did:key:zQ3shv5VUAbtY5P1jGsPzy7L27FTxeDv2hnhVp9QT3ALNCnQ2",
  "timestamp": "2023-06-21T14:47:48.935Z",
  "data": "Hello World!",
  "language": {
    "address": "literal"
  },
  "proof": {
    "valid": true,
    "invalid": false
  }
}

For now we have only created something we could call objective data. What we mean with this is that any agent with the URL of the Expression will be able to resolve it.

In the next chapter we will learn how to organize these expression in something called Perspectives. These are essentially local graph databases that in turn can be turned into Neighbourhoods (Shared social spaces).

Agents Languages