How to Analyze Audit Log Data

The ODK audit log records interview events such as question visits and timing. With the relevant parameters enabled, it can also record answer changes, user identity, and periodic device locations. DataSnap converts available audit evidence into report views for workflows like curbstoning detection and enumerator performance monitoring.

Audit logging must be enabled in the XLSForm before data collection begins. It cannot be added retroactively.

What the audit log captures

Data point	What it tells you
Question visit times	How long the enumerator spent on each question
Answer edits	Recorded response changes when track-changes=true
GPS coordinates	Periodic device locations when location tracking is enabled
User identity	Which enumerator collected the interview (if identify-user=true)
Location changes	Whether the device moved during the interview

Step 1: Enable the audit log in your XLSForm

Add an audit row to the survey sheet of your XLSForm:

type    | name  | parameters
--------|-------|------------
audit   | audit |

This is the minimum required configuration and records basic audit events. Add location parameters when the study needs GPS evidence.

For full audit capability, add parameters:

type  | name  | parameters
------|-------|----------
audit | audit | track-changes=true identify-user=true location-priority=balanced location-min-interval=60 location-max-age=120

Parameter reference:

Parameter	Description	Recommended value
track-changes	Record when answers are edited	true
identify-user	Record the enumerator's ODK username	true
location-priority	GPS accuracy vs battery usage	balanced
location-min-interval	Minimum seconds between GPS readings	60
location-max-age	Maximum age of an acceptable GPS reading (seconds)	120

Step 2: Add the audit row using LooprAI

In LooprAI Workspace, type:

Add audit logging with track-changes, identify-user, and GPS tracking enabled

LooprAI inserts the audit row with the recommended parameters automatically.

If you are still building the form, see How to Convert a Word or PDF Questionnaire Using LooprAI for the full workspace flow.

Step 3: Collect data with audit logging enabled

Deploy the updated XLSForm to your ODK server. Enumerators must delete and re-download the form on their devices to get the updated version with audit logging.

If you need a hosted ODK Central instance first, follow Getting a Server.

Step 4: Export the audit log from ODK Central

In ODK Central:

1. Go to your form's Submissions tab
2. Click Download → All data
3. Select CSV — this exports two files: submissions.csv and audit.csv
4. Download both files

Step 5: Upload to DataSnap

In SurveyLoopr DataSnap:

1. Create a new report (or edit an existing one)
2. Upload the audit.csv file.

DataSnap processes the audit file and populates the audit analysis section. See DataSnap reports for the audit-log workflow, evidence boundaries, and the one-report free starting point.

For the full report workflow, see Creating a DataSnap Report.

Step 6: Read the audit analysis in DataSnap

Current DataSnap reports include these sections when the source contains the required evidence:

Overview

Review total interviews, average and median duration, flagged interviews, and active days. These metrics summarize the report; they do not rank enumerators.

Activity and time use

Use surveys per day, the daily time-use heatmap, and time by an available group or variable to review recorded collection activity. Interpret timing patterns against the study schedule, travel, connectivity, and field protocol.

Question and interview review

Question friction, flagged interviews, and interview details help a team choose records for contextual review. A flag is a prompt to investigate, not proof of fabrication, misconduct, or poor performance.

Survey concentration map

When the audit file contains usable location evidence, DataSnap can plot the available interview GPS coordinates on a 3D map. Reports without usable GPS data do not show this view. The map does not score points against an expected study area or use location colors as a fraud verdict.

Audit patterns that warrant contextual review

ODK audit events can support questions beyond the current DataSnap sections. Inspect source audit data and operational records when you need evidence DataSnap does not render.

Pattern	Context to check
Durations outside the study's expected range	Form length, interruptions, training, or rushed work
Repeated coordinates when usable GPS exists	Sampling design, shared facilities, GPS precision, or field movement
Unusual answer-change sequences in source audit data	Form design, corrections, navigation, or coaching
Collection times outside the planned schedule	Time zone, device clock, travel, or field protocol
Unexpected usernames in source audit data	Assignment records, shared devices, or account use

These are review prompts, not diagnoses. Current DataSnap does not provide expected-area GPS scoring, universal edit-rate thresholds, or per-enumerator rankings.

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