The data dictionary
The data dictionary is your study’s schema: the list of fields you plan to collect about each record — whether that record is an enrolled participant or a sample. Everything else builds on it — profile forms place dictionary fields, onboarding flows fill them in, and every record stores its values against them. Define fields carefully once and your data stays consistent and comparable for the life of the study.
You need to be an owner or admin to add fields.
Field types
| Type | Holds | Validation you can add |
|---|---|---|
| Text | Free text | Minimum length, maximum length, pattern |
| Number | A number | Minimum value, maximum value |
| Date | A date | Earliest, latest |
| Yes / No | True or false | — |
| Select | One choice from a list | — |
| Multi-select | Several choices from a list | — |
Selects and multi-selects need at least one option; you can mark one option as the default. Each validation rule can carry its own error message, shown wherever the value is entered.
Creating a field
From your study, go to Fields → New. Give the field a name and type, and optionally a label (how it appears on forms), a categorisation (to group related fields), and guidance text. Mark it sensitive if it holds data that deserves extra care.
As you type a name, Indacas suggests similar fields that already exist — reusing one keeps your data comparable across studies, so prefer a suggestion over a duplicate.
Reusing fields
You rarely need to invent a field from scratch:
- The catalogue (Fields → Catalogue) lets you adopt ready-made system field definitions, or fields from your organisation’s dictionary, straight into the study.
- Sharing upwards: when creating a study field you can also add it to your organisation’s dictionary, so sister studies can adopt the same definition.
Every field shows its provenance — Custom, Organisation, or System — so you can tell at a glance which fields are shared definitions.