# Contextualisation

Variables in ENLYZE represent time series data extracted from a data source and linked to a specific machine. To make a variable available to services interacting with the ENLYZE Manufacturing Data Platform, you must first activate it. This guide explains how to explore variables, assign metadata, and activate them.

{% hint style="info" %}
What variables, time series, and the three variable statuses (Inactive, Exploration, Active) are is explained under [Variables & time series (Concepts)](/en/concepts/understanding-machine-data/variables-and-time-series.md).
{% endhint %}

## From Inactive to Exploration: Searching for Variables

The process of searching for variables to start exploring them, takes place in the [ENLYZE App](https://app.enlyze.com/). To choose inactive variables for exploration:

1. Navigate to [**Settings > Machines**](https://app.enlyze.com/settings/appliances)**.**

<figure><img src="/files/qCRRnN4Rdk1UlJCGarDz" alt="" width="563"><figcaption><p>Machine Settings Page</p></figcaption></figure>

2. Open the **Selection** section for the relevant machine.
3. Use the variable table to locate and select variables.
4. Move your selected variables listed on the right section to exploration using the `Explore` button.

### Available Filters

<figure><img src="/files/EUr5TsIxeOFiGRAzNdBb" alt="" width="563"><figcaption><p>Variable Selection Section</p></figcaption></figure>

* **Include/Exclude by Keyword**

  Use keywords to include or exclude variables. These filters apply to the `Origin Name`, `Display Name`, and `Comment` fields.

<figure><img src="/files/BUaEc79dldC4B0xNPtzZ" alt="" width="331"><figcaption></figcaption></figure>

* **Data Type and Status**

  Filter variables by type: *string, numerical or boolean*.

  Filter variables by status:

  * :dark\_sunglasses: Binoculars = Exploration
  * 💎 Diamond = Active

<figure><img src="/files/h40JjIdOu4gl03iywu7S" alt="" width="233"><figcaption></figcaption></figure>

* **Data Source Filter**

  Each variable lists its origin in the `Data Source Name` column. Use this filter to narrow your search to specific sources.

Once you've selected variables for exploration, they appear in the right-hand panel. Click `Explore` to change their status to Exploration.

## From Exploration to Active: Contextualizing Variables

<figure><img src="/files/bAIfWlgBV94IftXbrdWX" alt="" width="563"><figcaption><p>Variables in Exploration</p></figcaption></figure>

You can manage variables in exploration under:

> **`Settings > Machines > Your_Machine > Selection > Exploration`**

This view allows you to preview the variable’s values over time. Use the **Time Picker** in the top-right corner to adjust the visible time range.

{% hint style="warning" %}
**Important**\
Data collection begins only after a variable is set to **Exploration**. No values are available from before that point. You can see how long a variable has been in this status via the indicator in the top-right of each variable card.
{% endhint %}

### Activating a Variable

To activate a variable:

1. Assign a **display** **name**. This name will be the one used by external services.
2. Set a **scaling factor** (if required).
3. Configure the **unit**.

Click `Take Over` to activate the variable. It will disappear from the exploration list and move to active.

### Discarding a Variable

If you no longer wish to explore a variable, you can discard it. This removes all collected data but the variable can still be found in the selection table.

## Managing Active Variables

<figure><img src="/files/25kTuuzstMEBscowTWbj" alt="" width="563"><figcaption><p>Overview of Active Variables</p></figcaption></figure>

Access active variables via:

> **`Settings > Machines > Your_Machine > Overview`**

You can:

* Edit variable metadata using the **Edit** button in the right-most column.
* **Deactivate** a variable, which deletes its historical data and removes it from the overview.

## Related topics

Only in German

{% embed url="<https://www.enlyze.com/stories/euromap-standards-datenblocke-tags-harmonisierten-daten>" %}

{% embed url="<https://www.enlyze.com/stories/daten-harmonisierung-visualisieren-kontextualisieren-namensschema>" %}


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