This topic covers using the Field Editor, the user interface for defining and editing the fields that represent columns in a grid of data. The set of fields, also known as the schema or "domain", describes the shape of data. Each field, or column, has a main field type and can also have various properties and settings to control display and behavior of the data in that column.

The field editor is a common tool used by many different data structures in LabKey. The method for opening the field editor varies by data structure, as can the types of field available. Specific details about fields of each data type are covered in the topic: Field Properties Reference.

Topics:

- Open the Field Editor - Create New Fields -- Import or Infer Fields from File -- Manually Define Fields - Edit Fields -- Rearrange Fields -- Delete Fields - Edit Field Properties and Options: Expand field details. -- Type Specific Formatting Options are covered in the topic: Field Properties Reference -- Name and Linking Options -- Conditional Formatting and Validation Options - Advanced Settings - Export Sets of Fields (Domains)

Open the Field Editor

How you open the field editor depends on the type of data structure you are editing.

Data StructureOpen for Editing Fields
ListOpen the list and click Design in the grid header
DatasetIn the grid header, click Manage, then Edit Definition, then the Fields section.
Assay DesignSelect Manage Assay Design > Edit Assay Design, then click the relevant Fields section
Sample TypeClick the name of the type and then Edit Type
Data ClassClick the name of the class and then Edit
Study PropertiesGo to the Manage tab and click Edit Additional Properties
Specimen PropertiesUnder Specimen Repository Settings, click Edit Specimen/Vial/Specimen Event Fields
User PropertiesGo to (Admin) > Site > Site Users and click Change User Properties
Issue DefinitionsViewing the issue list, click Admin.
Query MetadataGo to (Admin) > Go To Module > Query, select the desired schema and query, then click Edit Metadata

If you are learning to use the Field Editor and do not yet have a data structure to edit, you can get started by defining some additional study properties as shown in the walkthrough of this topic. By default, there are no additional properties predefined in a study.

- Follow the instructions in this topic to install an example study if you don't already have a study to work with. - In your study, click the Manage tab. - Click Edit Additional Properties.

Create New Fields

To use the Field Editor to create a new set of fields and their properties, you can follow this example for defining additional study properties.

- Open your data structure for editing. - To get started, decide how you want to define the first fields: -- Import or infer fields from file: The supported formats are shown below the upload panel. --- In the case of study properties, shown in our example here, inferral is not available so the link reads "Import fields from file" instead. -- Manually Define Fields: Click the button to open the manual field editor.

Both options are available when the set of fields is empty. Once you have defined some fields by either method, the manual editor is the only option for adding more fields.

Import or Infer Fields from File

- When the set of fields is empty, you can import (or infer) new fields from a file. -- The range of file formats supported depends on the data structure. Some can infer fields from a data file; all support import from a JSON file that contains only the field definitions. -- In the case of additional properties, shown above, JSON is the only accepted format. -- When a JSON file is imported, all valid properties for the given fields will be applied. See below. - Click to select or drag and drop a file of an accepted format into the panel. - The fields inferred from the file will be shown in the manual field editor, where you may fine tune them or save them as is.

Manually Define Fields

- After clicking the Manually Define Fields button, the panel will change to show the manual field editor. - Depending on the type of data structure, and whether you started by importing some fields, you may see a first "blank" field ready to be defined. - If not, click Add Field to add one.

- Give the field a Name. If you enter a field name with a space in it, you will be warned that SQL queries, R scripts, and other code are easiest to write when field names only contain combination of letters, numbers, and underscores, and start with a letter or underscore. - Use the drop down menu to select the Data Type. -- The data types available vary based on the data structure. Learn which structures support which types here. -- Each data type can have a different collection of properties you can set. -- Once you have saved fields, you can only make limited changes to the type. - You can use the checkbox if you want to make it required that that field have a value in every row.

- Continue to add any new fields you need - one for each column of your data. - Click Save to save and exit the editor.

Edit Fields

To edit fields, reopen the editor and make the changes you need. If you attempt to navigate away with unsaved changes you will have the opportunity to save or discard them. When you are finished making changes, click Save.

Once you have saved a field or set of fields, you can change the name and most options and other settings. However, you can only make limited changes to the type of a field. You can change among text types, but cannot change a text field into a number or a boolean, for example.

Rearrange Fields

To change field order, drag and drop the rows using the six-block handle on the left.

Delete Fields

To delete a field, click the icon. It is available in both the collapsed and expanded view of each field and will turn red when you hover.

If you have not yet saved the set of fields, i.e. if you are in the process of creating a domain and make a mistake, clicking the icon will immediately delete the field.

If you have already saved the set of fields, you will be asked to confirm the deletion and reminded that all data in a deleted field will be deleted as well. Removing a field cannot be undone.

Click Save when finished.

Edit Field Properties and Options

Each field has a data type and can have additional properties defined. The properties available vary based on the field type. Learn more in this topic: Field Properties Reference

To open the properties for a field, click the icon on the right (it will become a handle for closing the panel). For example, the panel for a text field looks like:

Fields of all types have: - Name and Linking Options - **Conditional Formatting and Validation Options - Advanced Settings

Most field types have a section for **Type-specific Field Options: The details of these options as well as the specific kinds of conditional formatting and validation available for each field type are covered in the topic: Field Properties Reference.

Name and Linking Options

All types of fields allow you to set the following properties: - Description: An optional text description. This will appear in the hover text for the field you define. XML schema name: description. - Label: Different text to display in column headers for the field. This label may contain spaces. The default label is the Field Name with camelCasing indicating separate words. For example, the field "firstName" would by default be labelled "First Name". If you wanted to show the user "Given Name" for this field instead, you would add that string in the Label field. - Import Aliases: Define alternate field names to be used when importing from a file to this field. This option offers additional flexibility of recognizing an arbitrary number of source data names to map to the same column of data in LabKey. Multiple aliases may be separated by spaces or commas. To define an alias that contains spaces, use double-quotes (") around it. Learn more about import aliases. - URL: Use this property to change the display of the field value within a data grid into a link. Multiple formats are supported, which allow ways to easily substitute and link to other locations in LabKey. The ${ } syntax may be used to substitute another field's value into the URL. Learn more about using URL Formatting Options.

Conditional Formatting and Validation Options

All fields offer conditional formatting criteria. String-based fields offer regular expression validation. Number-based fields offer range expression validation. Learn about options supported for each type of field here.

- Conditional Formatting - Regular Expression Validation - Range Validators

Create Conditional Format Criteria

- Click Add Format to open the conditional format editor popup.

- Specify one or two Filter Type and Filter Value pairs. - Select Display Options for how to show fields that meet the formatting criteria: -- Bold -- Italic -- Strikethrough -- Text Color: Choose from the picker or type into the #000000 area to specify a text (or fill) color to use. -- You will see a preview of text on the right. - Add an additional format to the same field by clicking Add Formatting. A second panel will be added to the popup. - When you are finished defining your conditional formats, click Apply.

Create Regular Expression Validator

- Click Add Regex to open the popup.

- Enter the Regular Expression that this field's value will be evaluated against. All regular expressions must be compatible with Java regular expressions as implemented in the Pattern class. - Description: Optional description. - Error Message: Enter the error message to be shown to the user when the value fails this validation. - Check the box for Fail validation when pattern matches field value in order to reverse the validation: With this box unchecked (the default) the pattern must match the expression. With this box checked, the pattern may not match. - Name: Enter a name to identify this validator. - You can use Add Regex Validator to add a second condition. The first panel will close and show the validator name you gave. You can reopen that panel using the (pencil) icon. - Click Apply when your regex validators for this field are complete. - Click Save.

Create Range Expression Validator

- Click Add Range to open the popup.

- Enter the First Condition that this field's value will be evaluated against. Select a comparison operator and enter a value. - Optionally enter a Second Condition. - **Description**: Optional description. - Error Message: Enter the error message to be shown to the user when the value fails this validation. - Name: Enter a name to identify this validator. - You can use Add Range Validator to add a second condition. The first panel will close and show the validator name you gave. You can reopen that panel using the (pencil) icon. - Click Apply when your range validators for this field are complete. - Click Save.

Advanced Settings for Fields

Open the editing panel for any field and click Advanced Settings to access even more options:

- Display Options: Use the checkboxes to control how and in which contexts this field will be available. -- Show field on default view of the grid -- **Show on update form when updating a single row of data** -- Show on insert form when updating a single row of data -- **Show on details page for a single row**


- Default Value Options: Automatically supply default values when a user is entering information. -- Default Type: How the default value for the field is determined. Options: --- Last entered: (Default) If a default value is provided (see below), it will be entered and editable for the user's first use of the form. During subsequent uploads, the user will see their last entered value. --- Editable default: An editable default value will be entered for the user. The default value will be the same for every user for every upload. --- Fixed value: Provides a fixed default value that cannot be edited. -- Default Value: Click Set Default Values to set default values for all the fields in this section of the assay design.


- Miscellaneous Options: -- **PHI Level**: Use the drop down to set the Protected Health Information (PHI) level of data in this field. --- Learn more in this topic: Protecting PHI Data --- (Premium Feature) Learn about using PHI Levels to mask data in the user interface in this topic: Compliance: Setting PHI Levels on Fields -- Exclude from "Participant Date Shifting" on export/publication: (Date fields only) If the option to shift/randomize participant date information is selected during study folder export or publishing of a study, do not shift the dates in this field. Use caution when protecting PHI to ensure you do not exempt fields you intend to shift. -- Make this field available as a measure: Check the box for fields that contain data to be used for charting and other analysis. These are typically numeric results. Learn more about using Measures and Dimensions for analysis. -- Make this field available as a dimension: Check the box for fields of non-numerical categories that can be included in a chart. Dimensions define logical groupings of measures. Learn more about using Measures and Dimensions for analysis. -- Make this field a recommended variable: Check the box to indicate that this is an important variable. These variables will be displayed as recommended when creating new charts or reports. -- Track reason for missing data values: Check this box to enable the field to hold special values to indicate data that has failed review or was originally missing. Administrators can set custom Missing Value indicators at the site and folder levels. Learn more about using Missing Value Indicators.

Export Sets of Fields (Domains)

Once you have defined a set of fields (domain) that you want to be able to save or reuse, you can export it by clicking (Export).

A Fields_*.fields.json file describing your fields as a set of key/value pairs will be downloaded. All properties that can be set for a field in the user interface will be included in the exported file contents. For example, the basic text field named "FirstField" we show above looks like:

[
{
"conditionalFormats": [],
"defaultValueType": "FIXED_EDITABLE",
"dimension": false,
"excludeFromShifting": false,
"hidden": false,
"lookupContainer": null,
"lookupQuery": null,
"lookupSchema": null,
"measure": false,
"mvEnabled": false,
"name": "FirstField",
"propertyValidators": [],
"recommendedVariable": false,
"required": false,
"scale": 4000,
"shownInDetailsView": true,
"shownInInsertView": true,
"shownInUpdateView": true,
"isPrimaryKey": false,
"lockType": "NotLocked"
}
]

You can save this file to import a matching set of fields elsewhere, or edit it offline to reimport an adjusted set of fields.

For example, you might use this process to create a dataset in which all fields were marked as measures. Instead of having to open each field's advanced properties in the user interface, you could find and replace the "measure" setting in the JSON file and then create the dataset with all fields set as measures.

Note that importing fields from a JSON file is only supported when creating a new set of fields. You cannot apply property settings to existing data with this process.

Related Topics

- Field Properties Reference - Protecting PHI Data - Measure and Dimension Columns

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