Selecting a Variable Type

Choose Variable Type

From the Form Design > Variables screen, select the button to open the Choose Variable Type dialog.

Select between entering the initial value of a variable manually, or by SQL query.

This menus allows you to specify the initial value of a variable manually or via SQL statement.

Manual variable - manually specifies the data type and value of the variable and any sub-variables. More information on this menu can be found on the Variables page.
SQL statement - opens the SQL editor where you can free type or use the Visual Designer to construct your query. More information specific to the SQL statement option can be found on the SQL Editor page.

Choice Entry

The Choice Entry screen can be accessed from Form Design > Properties > Choices by selecting the ellipses from within the Choices field, or by double clicking on an object within the form. Similar to the Choose Variable Type screen, the choices here are Manual entries for manual input of the data that will appear in the selected object, or SQL statement to populate the data used by the object via a SQL query.

Select how to populate the data within your object - either by manual input, or via SQL query.

Manual Entries

Manually add, edit, or delete columns for your dashboard object.

Here you can select the Add Column, or Edit Column buttons to open the Column Properties menu. To delete a column from the field, select the Delete Column button.

Note: when selecting Manual entries via a multi-column list box, the Import From File option becomes available. This option allows you to populate a multi-column list box with data from an imported .csv file.

The Import From File option only appears when manually inputting the data of a multi-column list box.

Adding or editing a column opens the Column Properties menu.

Manually input your column data.

Name - the Argos variable name.
Display Caption - the name as it will be displayed when the DataBlock is run. If this field is left blank, it will default to the variable name.
Column Description - a brief description of the data within the column.
Conditional Formatting - used to add emphasis or context to the text or cells within a list box. For more information see the conditional formatting page.
Visible - sets the visibility of the column header.
Width - set the fixed width of the column header.
Alignment - specify left, right, or center alignment within the cell.

If you've manually added multiple columns to a list box, the next screen will ask you to select which field you'd like displayed in that object when the DataBlock is run.

For single column list boxes that have had multiple columns added, select which column should be visible in this lost box when running the DataBlock.

Prompt for Data

When accessing the Choice Entry dialog via a multi-column list box, the Prompt for Data option becomes available.

The Prompt for Data option allows MAPS administrators to request a .csv file be upload when a user next opens to DataBlock.

DataBlock Designers may select this option to request a .csv file be uploaded by a DataBlock runner the next time the DataBlock is run. This is useful for supplementing a query with information found outside of a typical database.

From this screen, DataBlock Designers may define the fields displayed in the multi-column list box based on a CSV file imported by the end user executing the dashboard.

Here, the MAPS admin may include which Csv headers they expect to be inlcuded in the .csv file uploaded by the user. They may also mark these files as required, and inlcude a custom message inlcuded in the prompt.

Under Expected fields, column headers can be added, deleted, or edited via the Add, Delete, and Edit buttons. Likewise, Designers can simply upload their own .csv file via the Upload from file button to auto-fill the expected header fields.

Under Additional options, a custom message may also be included. This custom message will display along with the request for data when the DataBlock is next run.

Selecting Add or Edit brings up the Column Properties menu, where more options may be configured.

Here the MAPS admin can specify the CSV Column Headers to be expected via the user's uploaded .csv file.

CSV Column Header Name - the name of the column header.
Required - check this box to mark this header as a required field in the CSV upload.
Name - the Argos variable name.
Display Caption - the name as it will be displayed when the DataBlock is run. If this field is left blank, it will default to the variable name.
Column Description - a brief description of the data within the column.
Format - allows you to apply a format mask on a numeric or date field. For example, you can change the way the date is displayed or adding dollar signs and decimals.
Conditional Formatting - used to add emphasis or context to the text or cells within a list box. For more information see the conditional formatting page.
Visible - sets the visibility of the column header.
Width - set the fixed width of the column header.
Alignment - specify left, right, or center alignment within the cell.

Next, you'll be able to preview the columns and make any further adjustments if necessary.

Preview the expected fields.

When the DataBlock is next run, the DataBlock runner will receive the following:

The next user to open the DataBlock will receive this prompt asking for a .csv file uplaod, along with a custom message from their MAPS administrator.

Missing Required Fields

When a CSV header is marked as required by the DataBlock Designer, but is missing from the prompted user's upload, the following message is produced:

Failing to upload the required files results in this message.

This message informs the DataBlock runner that some data could not be mapped during the .csv upload, as the header names were either missing or did not match those that were marked as required by the DataBlock Designer. Headers preceded by an asterisk in the left column are those that are required, while those that are missing from the upload are enclosed in parentheses in the right column.

In the event that your header names don't match but the data is the same, selecting the missing header on the right allows you to match it with one of the required headers and convert it into the correct header name.

Note: if a header name is not marked as required, and the intended header name doesn't match when uploaded, the value may populate in the multi-column list box as null.