5. Viewing Data



From the website

You can directly view participant data, both survey and sensor, from the Data section of a study, on the ODIN Researcher UI:
Every dataset you retrieve from this page can be downloaded as a CSV, using the button at the top-right corner of the table.

Downloads

Data.

You can download the entirety of your study's data as a collection of CSV files. The zipped files will contain everything stored on our database.

Codebook.

It's also possible to download the study's codebook from this page, which includes a PDF summary of the survey, as well as a human-friendly CSV version of the actual data. For more info, take a look at  this guide⁠ .


Data visualizer

The ODIN website has a visualization module, from where you can access a quick overview of your participants' data:

Axis.

  • The x axis represents time (adjustable with the controls at the bottom).
  • The left-y axis indicates which coupon's data is being represented (adjustable with the controls at the left).
  • The right-y axis tells you which data type each line of segments (rectangles) corresponds to. You can toggle data types with the checkboxes.


Segments.

A segment represents the intersection of all three axis; i.e., how many data points there are for the intersecting coupon, data type and timespan.
  • A grey segment without a border means there's no data at all.
  • A segment with a colored border means there's at least 1 data point for that coupon and data type, within the given time frame.
  • The intensity of the segment's internal color signals how much data there is, relative to the whole dataset for that data type.

Here's a closer look:
On the above example, you can see that coupon vzugwowmga had no data on Monday 8th, but did have some on the next day.
Coupon ugtjkcilmu, on the other hand, had only 1 GPS data point on Tuesday 9th.

Once again, you can see that the intensity of the colors is relative to other analogous segments. For instance, look at the difference in intensity between ugtjkcilmu's single GPS reading and vzugwowmga's single answer.

You can always get a hint of what you're seeing by hovering over a segment, and also click on it to get a more detailed overview of the data.

Answer segments.

Answer segments are somewhat special. For starters, not all answers are created equal. When getting a question, a participant may reply directly, by opening the ODIN app, writing a reply and submitting the answer. But they may also leave their phone on the side until the answer expires. Or they may submit an empty response; or even turn their phone off altogether. For this cases, ODIN still records the answer as a special case, namely expired, skipped or unset.
Since the visualization is about giving you a quick glance of the health of your coupons, showing this kind of answer would be misleading. And therefore the visualization module ignores them.


Health Metrics

Health metrics are per-coupon measurements aimed at making anomaly detection and data monitoring easier. At the time of writing we have support two types of metrics: expected vs. actual GPS readings and expected vs. actual answers.

Health metrics are only computed for studies that have the "Enable health metrics" option enabled, which can be set upon study creation:
Or edited on the About page of an existing study:

After having at least one day worth of data, and as long as it has the "Enable health metrics" option enabled, the study will automatically generate these measurements, which can be seen on the Health Metrics section:

Each measurement is calculated using a time interval relative to the Computation Date. For instance, the "Expected GPS readings" and "Actual GPS readings" measurements always go 24 hours into the past. The interval that each measurement considers can be seen on its info tooltip.

Let's look at a closer example by filtering the table to only show gurevshucy's metrics:
The last row's computation date is 2022-09-15 00:00:01.0, so that means that the expected and actual GPS readings are considering what we expected to receive from that coupon between 2022-09-14 00:00:01.0 and 2022-09-15 00:00:01.0.
We how what to expect because the GPS sensor has a sensor interval, which in this case is 5 minutes:
The actual GPS readings are just how many data points we got between those two dates. So this number would be equivalent to going to the Data page and retrieving the GPS readings for this coupon between 2022-09-14 and 2022-09-15.


Study Monitoring Reports

Study monitoring reports are automated daily summaries that help you track the health and progress of your study.


What Information Do Reports Contain?

1. Participant Overview

Each report starts with a summary of your study's participants:
  • New Participants: Lists any participants who registered on the monitoring date
  • Total Enrollment: Shows total participant count with platform breakdown (Android vs iOS)
  • Active Participants: Number of participants currently enrolled in the study (not yet expired)
Example:
Participants - jynzzplkev was added as a participant - Total participants are 19 (15 Android and 4 IOS), active participants right now: 2 (1 Android and 1 IOS)


2. Participant Performance Notes

The report lists participants (identified by their coupon codes) sorted by priority, with worst-performing participants appearing first. This helps you quickly identify who needs attention.
For each participant, the report shows:

Registration Information

  • Participant ID (coupon code)
  • Date they registered for the study

Engagement Status

  • Offline Detection: Whether the participant's device hasn't connected for the entire day
  • Study Completion: If the participant completed their study on that day

Question Response Metrics

  • Questions answered vs. questions asked for that day
  • Response rate percentage (daily)
  • Cumulative responses since registration
  • Specific issues:
  • Unresponsive: Participant didn't respond to a question before it expired
  • Skipped: Participant actively skipped a question

Sensor Data Collection (if applicable)

For studies collecting sensor data (GPS, Bluetooth, accelerometer, etc.):
  • Number of sensor readings collected vs. expected for the day
  • Collection rate percentage
  • Cumulative sensor data since registration
  • Separate metrics for GPS-triggered questions (if your study uses location-based surveys)

Report Scoring System

Participants are ranked by a priority score based on:
  • Lower question response rates = Higher priority (needs attention)
  • Lower sensor collection rates = Higher priority
  • Offline status = Highest priority
This means participants at the top of the report need the most attention, while those at the bottom are performing well.

Sample Report Interpretation

qizhncqnnq (registered: 2022-11-11) 
- Appears to be offline the entire day 
- Has answered 0 of 0 question(s) on 27 Nov (0%), 0 of 4 expected since registration (0%) 
- The GPS acquired 0 of 288 expected on 27 Nov (0%), 222 of 4510 expected since registration (5%)
What this tells you:
  • Participant qizhncqnnq registered on Nov 11
  • Their device has been offline all day on Nov 27
  • They've only collected 5% of expected GPS data since joining
  • Action needed: This participant likely needs technical support or re-engagement


jynzzplkev (registered: 2022-11-27)
- Unresponsive to question belonging_location at (01:34 PM) 
- Has answered 7 of 8 question(s) on 27 Nov (88%), 109 of 112 expected since registration (97%) 
- The GPS acquired 168 of 288 expected on 27 Nov (58%), 2175 of 2738 expected since registration (79%)
What this tells you:
  • Participant jynzzplkev registered on Nov 27 (same day)
  • Missed one question at 1:34 PM
  • Otherwise performing well with 97% overall question response rate
  • GPS collection at 79% is good
  • Action needed: Minor - possibly send a reminder about responding to all questions


How to Use These Reports

Daily Monitoring

Review reports each morning to:
    Welcome new participants
    Identify technical issues (offline devices, poor data collection)
    Spot engagement problems (skipped questions, low response rates)
    Track overall study health

Proactive Intervention

Use the reports to:
  • Contact participants who appear offline or have very low engagement
  • Provide technical support for sensor data collection issues
  • Send encouragement to participants with declining response rates
  • Verify study completion for participants whose study period ended


Key Metrics to Watch

Metric
Good Range
Concerning
Question Response Rate
>80%
<60%
Sensor Collection Rate
>70%
<50%
Participant Offline
<12 hours
>1 days

Getting Help

If you notice patterns of poor performance across multiple participants, this may indicate:
  • Technical issues with the study configuration
  • Unclear participant instructions
  • Issues with sensor permissions on devices
  • Study design problems (too many questions, poor timing, etc.)
  • Technical issues with the app
You may contact the ODIN team at your designated Slack channel or through our email at any point, at  odindevelopers2017@gmail.com