# Form Design Patterns _Practical patterns for combining field types in fieldwork forms._ --- ## Overview Once you have chosen the right field types for your data (see [Choosing a Field Type](field-selection-guide.md)), the next step is combining them into effective forms. This guide presents five composite patterns — recurring field combinations that solve common recording tasks — and worked examples from archaeology, ecology, and geology. Good form design favours recognition over recall: let users select from lists rather than remember codes. Use progressive disclosure to keep forms simple by default, revealing detailed fields only when needed. Maintain consistent interaction patterns throughout a {{notebook}} so that collectors learn the form once and can work quickly. For a complete list of available field types, see [Field Types](../index.md). ## Composite Patterns These five patterns appear across disciplines whenever fieldwork forms need to go beyond single-field recording. ### The Measurement Pattern When recording a measurement, combine: - A **Select one option** or **[Select Field](../choice-fields/select.md)** for the measurement type (e.g., length, width, depth). - A **Controlled Number** for the numeric value, with minimum and maximum bounds set to catch entry errors. - A unit indicator — either included in the field label (e.g., "Depth (cm)") or as a separate **Select one option** field if multiple units are possible. - An **Annotation** enabled on the number field for recording uncertainty, instrument used, or measurement conditions. ### The Identification Pattern When recording an identification that may be provisional, combine: - A **[Select Field](../choice-fields/select.md)** or **Select Field (Hierarchical)** for the identification (e.g., species, soil type, artefact class) drawn from a controlled vocabulary. - Use of "Uncertainty" if a simple "certain" vs. "uncertain" flag is all that is needed, **OR** - A **Select one option** for more nuanced confidence level (e.g., Certain, Probable, Possible, Unlikely). - A **[Checkbox](../choice-fields/checkbox.md)** labelled "Requires verification", conditionally revealed when confidence (selected through Select one option) is not Certain. - A **Multi-line Text Field** for detailed notes, conditionally revealed alongside the verification flag. ### The Complex Observation Pattern When structuring complex observations with multiple possible outcomes, combine: - A **Select one option** for the observation type, which acts as a branching gateway. - Type-specific field groups revealed conditionally based on the selection. - Standard metadata captured automatically by the platform (recorder, timestamp, location). - A **Take Photo** field with Annotation enabled for visual documentation. ### The Progressive Detail Pattern When a form needs to support both rapid and detailed recording, combine: - Basic fields that are always visible for quick recording. - A **[Checkbox](../choice-fields/checkbox.md)** as a gateway question (e.g., "Record detailed measurements?"). - Detailed fields conditionally revealed when the checkbox is ticked. This pattern keeps the form simple for routine records while still enabling depth when needed. ### The "Other" Specification Pattern When a controlled vocabulary needs an escape hatch for exceptions, combine: - A **[Select Field](../choice-fields/select.md)** or **Select one option** with an "Other" option included in the list. - A **[FAIMS Text Field](../text-fields/faims-text-field.md)** conditionally revealed when "Other" is selected, prompting the collector to specify. This preserves the structure of controlled data while allowing flexibility for unanticipated values. ## Discipline-Specific Examples The patterns above can be adapted to suit different fieldwork disciplines. The examples below illustrate common field combinations and human-readable identifier (HRID) structures. ### Archaeological Recording Archaeological forms typically need to capture stratigraphic relationships, contextual inheritance, and structured identifiers: - **Stratigraphic relationships** — Use **Add Related Record** with defined vocabulary pairs (e.g., "cuts / cut by", "fills / filled by", "above / below") to record temporal and physical relationships between contexts (temporal and physical relationships can be captured independently using multiple relationships). - **Contextual inheritance** — Finds inherit context properties, samples inherit environmental conditions, and photos inherit spatial coordinates through parent–child record relationships. - **HRID structure** — A typical archaeological identifier combines site, trench, entity type, and number: `SITE-TRENCH-FEATURETYPE-NUMBER` (e.g., "Perachora-T5-Hearth-023"). ### Ecological Survey Ecological survey forms often centre on transect-based observation and abundance estimation: - **Transect observations** — Use an **Auto Incrementing Field** for sequential observation points, combined with **Take point** for each location along a transect. - **Abundance estimation** — Use **Controlled Number** fields for percentage cover or species counts, or a **Select one option** field for categorical scales (e.g., DAFOR: Dominant, Abundant, Frequent, Occasional, Rare). - **HRID structure** — A typical ecological identifier combines transect, point, and date: `TRANSECT-POINT-DATE` (e.g., "T1-P5-20240315"). ### Geological Sampling Geological forms often involve deep sample hierarchies and orientation data: - **Sample hierarchies** — Use **Add Related Record** to maintain provenance through processing stages: Outcrop → Sample → Subsample → Analysis. - **Orientation data** — Use grouped **Controlled Number** fields for strike and dip measurements or plunge and trend for linear features. - **Sample identifiers** — Use QR / Barcode Scanner to scan a sample label in the field to avoid transcription errors (consider implementing IGSNs). - **HRID structure** — A typical geological identifier combines project, location, and sample: `PROJECT-LOCATION-SAMPLE` (e.g., "GEO2024-OUT3-S045").