diff --git a/content/concepts/did-ddo.md b/content/concepts/did-ddo.md
index ef1d97b9..7a467dc4 100644
--- a/content/concepts/did-ddo.md
+++ b/content/concepts/did-ddo.md
@@ -132,7 +132,7 @@ An asset of type `algorithm` has additional attributes under `metadata.algorithm
| ------------------------ | ------------------------------------------- | -------- | ------------------------------------------------------------------------------------------ |
| **`language`** | `string` | | Language used to implement the software. |
| **`version`** | `string` | | Version of the software preferably in [SemVer](https://semver.org) notation. E.g. `1.0.0`. |
-| **`consumerParameters`** | [Consumer Parameters](#consumer-parameters) | | An object the defines required consumer input before running the algorithm |
+| **`consumerParameters`** | [Consumer Parameters](#consumer-parameters) | | An object that defines required consumer input before running the algorithm |
| **`container`** | `container` | **✓** | Object describing the Docker container image. See below |
The `container` object has the following attributes defining the Docker image for running the algorithm:
@@ -212,7 +212,7 @@ Type of objects supported :
Description |
Example |
-'url' |
+url |
Static URL. Contains url and HTTP method |
@@ -238,7 +238,7 @@ First class integrations supported in the future :
| Example |
-"ipfs" | IPFS files |
+ipfs | IPFS files |
```json
@@ -252,10 +252,10 @@ First class integrations supported in the future :
|
-
"filecoin" | Filecoin storage | |
-"arwave" | Arwave | |
-"storj" | Storj | |
-"sql" | Sql connection, dataset is generated by a query | |
+filecoin | Filecoin storage | |
+arwave | Arwave | |
+storj | Storj | |
+sql | Sql connection, dataset is generated by a query | |
A service can contain multiple files, using multiple storage types.
@@ -444,11 +444,12 @@ Example:
#### Consumer Parameters
-Sometimes, you may need some input before downloading a dataset or running an algorithm.
+Sometimes, the asset needs additional input data before downloading a dataset or running an algorithm.
Examples:
-- You want to know the desired sampling interval of data in your dataset, before the user is going to download it. Your dataset URL is `https://example.com/mydata`. So you will define a field called `sampling`, ask the user to enter a value and then this parameter is going to be added to the URL of your dataset as query parameters: `https://example.com/mydata?sampling=10`
-- Before running an algorithm, you need to know how many iterations should it perform. You define a field called `iterations`, ask the user to enter a value and this parameter is stored in a specific location in your Computer-to-Data pod for the algorithm to read and use that value.
+- The publisher needs to know the sampling interval before the buyer downloads it. Suppose the dataset URL is `https://example.com/mydata`. The publisher defines a field called `sampling` and asks the buyer to enter a value. This parameter is then added to the URL of the published dataset as query parameters: `https://example.com/mydata?sampling=10`.
+
+- An algorithm that needs to know the number of iterations it should perform. In this case, the algorithm publisher defines a field called `iterations`. The buyer needs to enter a value for the `iterations` parameter. Later, this value is stored in a specific location in the Computer-to-Data pod for the algorithm to read and use it.
It's an array of elements, each element object defines a field.
An element looks like: