survey2ddi 0.1.0

Transform survey data (KoboToolbox, LimeSurvey) into DDI-adjacent formats

This repository is part of the Civic Data Lab's Survey Toolbox. In the Toolbox you'll find information and guidance on everything related to surveys — from design to analysis.

survey2ddi

Bridge the gap between raw survey exports and archival-grade metadata.

Survey platforms like KoboToolbox and LimeSurvey are excellent for data collection, but their raw exports are often difficult to use for long-term archiving or secondary analysis. They frequently lack clear labels, structured metadata, and standardized formats.

survey2ddi transforms these raw exports into a standardized pair of files:

1. DDI-Codebook 2.5 XML: A machine-readable schema containing all question texts, choice labels, and group structures. Compatible with the qwac question bank.
2. DDI-Aligned CSV: Clean response data where column headers match the XML variable names exactly, and multi-select questions are expanded into binary indicators.

Why use this?

• Long-term Archiving: Move away from cryptic CSVs to self-documenting DDI metadata.
• Interoperability: Import your survey structure directly into tools like qwac.
• Data Analysis: Use the generated XML to automatically apply labels to your data in R, Python, or Stata (see our example notebook).
• Reproducibility: Maintain a strict link between your data collection instrument (XLSForm/TSV) and the resulting dataset.

Setup

Requires Python 3.13+. Install with uv:

uv sync

Copy .env.example to .env and fill in your credentials.

Usage

1. Pull data from your platform

First, download the raw responses and structure from your survey platform.

KoboToolbox:

uv run kobo2ddi pull <asset_uid>

LimeSurvey:

uv run limesurvey2ddi pull <survey_id>
# Note: For LimeSurvey, also export your "Survey structure" (TSV) 
# and place it in the output folder as survey.tsv

2. Transform to DDI + CSV

Once the data is cached locally, generate the standardized outputs.

# KoboToolbox
uv run kobo2ddi transform <asset_uid>

# OR use a raw CSV export from the GUI instead of the API JSON
# (Must be exported with "XML values and headers" and use , or ; as delimiter)
uv run kobo2ddi transform <asset_uid> --data path/to/export.csv --title "My Study"

# LimeSurvey (uses cached responses.json + survey.tsv/form.xlsx)
uv run limesurvey2ddi transform <survey_id> --title "My Research Study"

# OR use a raw CSV export from the GUI instead of the API JSON
# (Must be exported with "Question codes" as headers)
uv run limesurvey2ddi transform <survey_id> --data path/to/export.csv --title "My Study"

The output will be saved in output/<id>/ as <id>.xml and <id>.csv.

Examples

We provide a basic example of the generated output and a Jupyter notebook showing how to use them for analysis in the examples/ directory.

To run the example notebook:

uv sync --group notebook
cd examples/basic
uv run jupyter notebook analysis_example.ipynb

Running tests

uv run pytest

Tests include XSD validation of generated XML against the official DDI-Codebook 2.5 schema (requires xmllint, auto-skipped if not available).

Integration tests (Schematron)

Schematron rules go beyond the XSD (uniqueness of IDs, consistency between variable groups and their members, _other conventions, etc.). They live in qwacback and are checked by a Java worker exposed behind POST /api/validate. The integration suite boots that stack via docker compose and posts generated XML to it.

uv run pytest -m integration

Requires Docker. The session fixture pulls ghcr.io/correlaid/qwacback{,-schematron-worker}:latest, waits for readiness, then tears the stack down. Cold start is ~20-30s; subsequent tests in the same session are ~1s.

To iterate faster, keep the stack up and point tests at it:

docker compose -f tests/integration/docker-compose.validate.yml up -d --wait
S2D_VALIDATE_URL=http://127.0.0.1:8090 uv run pytest -m integration

Pin to a specific qwacback build with QWACBACK_TAG=sha-abc1234 (or a semver like 0.1.0). Change PB_PORT if 8090 is taken.

Validating XML manually

xmllint --noout --schema tests/schemas/codebook.xsd output/<id>/<id>.xml

The schema files in tests/schemas/ are the official DDI-Codebook 2.5 XSD from the DDI Alliance.

Known limitations

Multi-language forms: Only the first label::* column in the XLSForm is used. For bilingual forms, place the preferred language column first.

Repeat groups: Variables inside begin_repeat/end_repeat blocks are silently skipped. KoboToolbox stores repeat data as nested arrays which require a different data model; this is not currently supported.

Plain groups in DDI XML: begin_group/end_group blocks without appearance="table-list" are not emitted as <varGrp> in the XML — their variables appear as standalone <var> elements. Groups with appearance="table-list" become <varGrp type="grid">.

LimeSurvey select_multiple bracket keys: LimeSurvey truncates option codes to 5 characters in its export (e.g. metall → metal). The transform recovers the original code via prefix matching. This fails if two choice codes share the same first 5 characters — a ValueError is raised in that case. It also fails silently (with a warning) if LimeSurvey uses internal answer codes that have no relation to the XLSForm choice names; this can happen for surveys not originally created from an XLSForm.

Design

The transform and DDI XML modules (kobo2ddi/transform.py, kobo2ddi/ddi_xml.py) are source-agnostic — they work with parsed XLSForm data rather than platform-specific objects. The LimeSurvey adapter (limesurvey2ddi/transform.py) normalises LimeSurvey's export quirks (underscore stripping, select_multiple sub-columns) before passing data to the same core functions.

As a Python library

# KoboToolbox
from kobo2ddi.client import KoboClient
from kobo2ddi.data import build_data_csv
from kobo2ddi.ddi_xml import build_ddi_xml
from kobo2ddi.transform import parse_xlsform, extract_variables

client = KoboClient()
asset = client.get_asset("your_asset_uid")
submissions = client.get_submissions("your_asset_uid")
survey_rows, choices, settings = parse_xlsform(Path("form.xlsx"))
xml_string = build_ddi_xml(asset["name"], survey_rows, choices, settings, submissions)

variables = extract_variables(survey_rows, choices)
csv_string = build_data_csv(variables, submissions)

# LimeSurvey
from limesurvey2ddi.transform import build_data_csv, build_ddi_xml

responses = [...] # from LimeSurvey API
xml_string = build_ddi_xml("My Survey", Path("form.xlsx"), responses)
csv_string = build_data_csv(Path("form.xlsx"), responses)