Array and Dataset Data Types
The Array and Dataset data types available on Tags allow for multiple data points to be stored in a single Tag. Configuring a Tag as an array or dataset is as easy as changing the data type in the Tag Editor.
Many OPC servers and drivers already support array type Tags, and now each element in the array can easily be represented with the array data types in Ignition. Additionally, array data types can be used with devices that do not support array types, and will instead expose each bit in the value. Because the core data type of each element in the array is the same, it is possible to apply Tag History, Alarming, or Scaling configurations onto the array, and these configurations will be inherited by each element.
Array Tag Write-Back
OPC Array Tags support writing back to the device. How this is done can vary, depending on the type of OPC Server in use. Some OPC Servers support writes to individual array elements, where a write would occur just like any other Tag write. However, some OPC Servers do not support individual element writes, which means the whole array will need to be written back to the array Tag, even if only a single element is changing.
Dataset Tags allow multiple rows and columns worth of data to be stored in a Tag. Each column is exposed as a separate folder in the Tag (i.e., the "name" folder in the image below). Dataset Tags can be driven by a query, so it's possible to query for multiple columns on a row in a single Tag. This is more efficient than using multiple query Tags (and thus multiple queries) to retrieve the same data.
While dataset tags are convenient, note that the Tag History system and Alarm system do not support tags with dataset types.

Valid data types that can be stored in dataset tags include the following:
- Float
- Short
- Long
- Date
- Integer
- Boolean
- String
- Color
- Double
- Timestamp
Dataset Tag Example
The following example will create a dataset memory Tag and display the contents in a Table component.
- Create a new Memory Tag. Name it Dataset, and change the data type to Dataset. The Dataset will be empty by default.
- Click the Edit
icon next to Value. The Value screen is displayed. For this example, we created a simple dataset with four columns and five rows. - Click the Add Column
icon. Name the first column City and set type to be String. - Click Add Column.
- Repeat adding columns as follows:
Column Name: Population Type: Integer
Column Name: TimeZone Type: String
Column Name: GMTOffset Type: Integer
Click the Add Row
icon. Add the row information as follows:
New York | 8368710 | EST | -5 |
Los Angeles | 3833995 | PST | -8 |
Chicago | 2853114 | CST | -6 |
Houston | 2242193 | CST | -6 |
Phoenix | 1567924 | MST | -7 |
Click the Commit button.
Click OK to save the Tag.
The Tag will now contain rows, columns, and values based on the configurations you made earlier in this example. Now you have a Tag with a dataset value that can be bound to by components in Vision and Perspective.