Defining your metadata
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We refer to the definition of your metadata as the schema. When you specify your schema you need to define the name and label. The name will be used to refer to the metadata using the API and the label defines the friendly name that will appear in Content Hub.
In the example below the label for the schema is "Tutorial Schema".
Your schema will contain one or more fields and for each you need to specify the name, label and type.
Note: the name of any field in your metadata cannot be the same as the name of the schema.
The following types of fields are supported:
integer (does not include decimals)
number (can include decimals)
boolean (this field type is also facetable. see the definition below).
Searchable and facetable strings
For string fields you should also consider if the field should be searchable or facetable.
If a string field is searchable it means that natural language searching is used for a full or partial string without the need to use wildcards. For example, if a field contains the string "spring collection" then searching for "spring", "coll" or "collection" will return the asset containing this string.
A facetable field is one that can be searched and filtered from a limited number of options. An example is a "color" field, where the range of available values is limited to the range of colors entered.
An example of filtering an asset using a facetable field in Content Hub is shown below. The facetable field is highlighted and one of the values available to search on was "brown". The assets returned from the search have "color" set to this value.
An indexable string can be searched, but only exact text matches will return the associated assets. You can also use wildcards (*) to do wildcard searching. All fields are indexable.
Defining string format
The format of a string will determine whether the field is searchable and facetable.
The following formats are supported for the string type:
symbol (use this to make the text facetable)
date-time (will display a UI in the field allowing user to choose date and time)
These string formats specify whether a string is indexable or facetable as shown in the table below.
Supplying the metadata
The process for adding the metadata to your account is as follows:
Define your metadata. Consisting of fields of the types shown above.
Send this to your Amplience technical consultant. See below for an example schema.
The technical consultant will use the information you provided to add the metadata to your account.
You can then test the metadata to make ensure that it meets your requirements.
In this example we want to add the following metadata: color, original price and sale price. The original price and sale price will be retrieved from an inventory system and updated during a sale promotion. The schema name will be "tutorial_schema" and the label (as it appears in Content Hub) is "Tutorial Schema".
The Original and sale price fields should be of type number.
The color field should be facetable, so it is defined as a string type with format symbol.
The schema can be defined as follows (you may find it easiest to send it to us in a spreadsheet or whatever format you find convenient):
Schema name: tutorial_schema Property: name: original-price label: "Original Price"type: number Property name: sale_price label: "Sale Price" type: number Property name: color label: "Color" type: string format: symbol
Once a metadata schema has been added to your account it cannot be deleted, so it is worth spending time on the definition of your schema before asking for it to be added to your account.
Your technical consultant will use this information to add the metadata schema to your account.