This guide explains how to view and interpret test results in Meridia Verify, including how to review the Results dashboard, understand risk severity, check which tests were applied, explore results in table and map views, and inspect affected farm plots in more detail.
Introduction
Meridia Verify runs different tests to help users understand the risk condition of an uploaded dataset from both a compliance and data quality perspective. These tests are grouped into two main categories: Compliance Tests and Data Quality Tests.
Two Types of Tests
Compliance Tests assess specific data aspects that may indicate the risk of non-compliance with the EU Regulation on Deforestation-free Products (EUDR). These tests cover issues such as deforestation, protected areas, land rights, and other compliance-related indicators.
Data Quality Tests assess the reliability and trustworthiness of the dataset itself. These tests help identify whether the data is suitable for analysis, especially for EUDR-related workflows where accurate farm location, geometry, and farmer information are important.
Understanding Test Types and Risk Severity Levels
Low risk: From a data quality perspective, this means that no material data quality issues were identified. From a compliance perspective, the tests did not detect anything that indicates a non-compliance issue with the farm record.
Medium risk: From a data quality perspective, this means that some issues were identified in the farm record. These issues may affect the accuracy of the analysis, but they do not cause a material decrease in reliability. From a compliance perspective, this may indicate weak evidence that a compliance issue could exist. Further investigation is recommended.
High risk: From a data quality perspective, this means that substantial issues were identified in the farm record, resulting in a serious decrease in reliability. Accurate analysis may not be possible. From a compliance perspective, the tests found strong evidence that the farm plot may not be considered compliant. Immediate investigation is recommended.
Critical risk: From a data quality perspective, this means that significant material issues were identified in the farm record. The farm record may need to be invalidated or excluded from the dataset. From a compliance perspective, this means there is significant evidence that the farm record is not compliant. Immediate action should be taken, including excluding produce from the affected farm plot, notifying relevant parties, and starting an investigation.
Invalid Result / N/A: From a data quality perspective, this means that the farm record is missing data required for a specific test, so the test could not produce a valid result. The missing data should be addressed. The urgency depends on the type of missing data, for example missing geometry is more urgent than a missing mapping date. From a compliance perspective, an N/A result may indicate that serious data quality issues made the analysis impossible.
How to View and Understand Test Results
Step 1 — Open the dataset results
Go to the “Datasets” page from the left-side navigation menu under “Verify & analyse”.
Find the dataset you want to review. You can use the dataset name, commodity, origin, upload date, number of records, test profile, or status to identify the correct dataset.
Once you have found the dataset, click the “Results” button on the right side of the dataset row. This will open the results dashboard for that dataset.
Step 2 — Review the Results dashboard
After clicking the “Results” button, you will be taken to the Results dashboard for the selected dataset.
This page gives you a high-level overview of the dataset’s test results. At the top, you can see key dataset information, including the origin, commodity, test profile, total farm plots, and the number of tests applied.
The dashboard also shows the overall profile risk distribution, which helps you understand how many farm plots are classified as Critical, High, Medium, or Low risk.
Below the summary section, you can review the main issues detected in the dataset, such as Top compliance issues or Top data quality issues. From this section, you can continue to explore the results in more detail by using options such as Info & Resolutions, View on Map, View Farm Plots, or Generate Report.
Point 1 — Review the dataset summary and risk overview
At the top of the Results dashboard, you can review the main summary of the selected dataset. This section helps you quickly understand the dataset context and its overall risk condition.
In this section, you can see several key details:
Origin: the country where the dataset comes from.
Commodity: the commodity type assessed in the dataset.
Test Profile: the test profile version used for the assessment, for example EUDR v1.10.
Total Farm Plots: the total number of farm plots included in the dataset.
Tests Applied: the number of tests that were successfully applied to the dataset compared with the total number of available tests.
For example, if the dashboard shows 34 / 37 under Tests Applied, it means that 34 tests were applied to the dataset out of 37 available tests. You can click “Details” to see more information about which tests were applied.
Below the dataset summary, you can also see the Profile risk distribution. This gives an overview of how farm plots are distributed across different risk levels, such as Critical, High, Medium, and Low.
You can use the dropdown menu to switch between different risk views:
Profile risk shows the original risk distribution based on the Verify methodology before any reclassification is applied.
Reclassified risk shows the updated risk distribution after farm plots have been reviewed and reclassified. This is useful when a result is considered a false positive and supporting evidence has been provided to correct or adjust the original test outcome.
This section is useful as a first checkpoint because it gives you a quick overview of the dataset condition before you explore specific compliance issues, data quality issues, or individual farm plots.
Checking which tests were applied
From the dataset summary, you can click “Details” next to “Tests Applied” to see which tests were run for the dataset.
The Tests applied window shows two main views:
Applicable tests
This tab lists the tests that were applied to the dataset. For each test, you can see the test code, test name, test group, and the Info & Resolutions button.
Not applicable tests
This tab lists the tests that were not applied to the dataset. A test may be skipped if the dataset does not meet the required upload criteria for that test, for example when specific data fields are missing or when certain checks are disabled.
Each test also includes a Test Group, such as Data Quality or Compliance. This helps you understand whether the test is related to the reliability of the dataset or to EUDR compliance risk.
You can also click “Info & Resolutions” to open more information about a specific test, including what the test checks and what actions may be needed to address the issue.
Point 2 — Review top compliance and data quality issues
Below the dataset summary, you can review the main issues detected in the dataset. This section helps you understand which tests are contributing most to the dataset’s risk profile.
You can switch between two views:
Top compliance issues
This view shows issues related to EUDR compliance risks, such as potential overlap with deforestation areas, protected areas, concession zones, or other compliance-related indicators.
Top data quality issues
This view shows issues related to the reliability and usability of the dataset, such as mapping accuracy, farm plot boundaries, geometry validity, or farmer identification.
Step 3 — Open the Table view
To review the test results in a more detailed tabular format, click the “Table” tab at the top of the Results dashboard.
The Table view shows the original Verify risk assessment and organizes the results by risk score, such as:
Critical Risks
High Risks
Medium Risks
Low Risks
In this table, each row represents a specific test result. You can review the test code, test name, test group, and the number of affected farm plots.
The Test Group column helps you identify whether the test belongs to Compliance or Data Quality.
From this view, you can also take follow-up actions:
Info & Resolutions
Open more information about the selected test, including severity thresholds, test explanation, and recommended resolution steps.
View Farm Plots
Open the list of farm plots affected by the selected test. This view is useful when you want to compare test results more systematically and understand which issues are contributing to each risk category.
Option 1 — Open “Info & Resolutions”
Click “Info & Resolutions” to understand why a specific test was triggered and what actions can be taken.
In this window, you can review three main sections:
Severity Thresholds
Shows how the test result is classified into Critical, High, Medium, or Low risk. For example, in DEF04, a farm plot may be classified as Critical if the overlap with deforestation area is above the defined threshold.
Test Info
Explains what the test checks and why the issue matters.
Resolutions
Provides recommended follow-up actions. These may include desk research, checking satellite imagery, comparing data sources, field verification, remapping farm plots, reclassifying false positives, or excluding confirmed non-compliant plots from the EU supply chain.
This option is useful when you want to understand the logic behind a test result before deciding what action to take.
Option 2 — View on Map
If you click “View Farm Plots” from the Table view, you will be taken to the Farm plots page.
On this page, you can review the affected farm plots in more detail. You can also adjust the displayed data by changing the selected dataset, test, geometry, and other available filters or attributes. This helps you narrow down the results and focus on the farm plots you want to review.
On the right side of each row, you will see a View on Map button. Click this button to open the spatial visualisation of the selected farm plot on the map.
This option is useful when you want to move from the tabular results into a map-based view and inspect the location and geometry of specific farm plots more closely.
Option 3 — Review the farm plot on the map
After clicking the View on Map button, the selected farm plot will open in the map view.
In this view, you can visually inspect the farm plot location, boundary, and overlap with relevant risk layers. The map shows the selected farm plot together with supporting layers such as deforestation areas, protected areas, exception areas, indigenous people areas, and country boundaries.
On the left side, the Legend and Layers panel allows you to turn map layers on or off. This helps you compare the farm plot boundary with the relevant risk layers more clearly.
On the right side, the farm plot information panel shows the selected farm plot ID, the triggered test, the risk level, overlap information, farmer details, aggregator, and the profile, compliance, and data quality risk scores.
This view is useful for visually checking whether a test result makes sense spatially before deciding whether further investigation, reclassification, or field verification is needed.
Step 4 — Open the Map view
After reviewing the results in the Table view, you can also open the Map tab to see the dataset spatially.
The Map view allows you to visualise farm plots and risk results directly on the map. This is useful when you want to understand where the risks are located and how they are distributed across the dataset area. At the top of the map, you can filter the displayed results by Risk Severity, such as All, Critical, High, Medium, Low, or N/A.
You can also use the filter options to refine what is shown on the map:
Filter by.
Allows you to filter results by group, such as all groups or specific test groups.
Select tes
Allows you to select a specific test and view only the farm plots related to that test.
The Legend and Layers panel can also be opened to manage the map layers and better understand the visual information shown on the map. This view helps you move from tabular results into a spatial overview of the dataset.
Step 5 — Use the Farm plots page for custom queries
You can also review test results from the Farm plots page. This page is useful when you want to build a more specific query across a dataset, depending on what type of farm plot information you want to check.
From the left-side navigation menu, click “Farm plots”. Then, select the dataset you want to review and adjust the available filters.
For example, based on the image, you can build a query using:
Dataset:
Dataset Testing – Resolution ReportTest:
DEF04 – Farm plot overlaps with deforestation area (commercial map)Risk level:
CriticalFilter by Farm Plot ID
Profile risk, Compliance risk, or Data quality risk
Reclassification outcome
After setting the filters, click “Apply Query” to update the results.
The results table will show the farm plots that match your query, including the farm plot ID, farmer ID, aggregator, reclassification status, and risk scores. This makes it easier to review specific farm plots across the selected dataset, compare their risk status, and decide whether they need further investigation, reclassification, or export.
Why test results matter
Data quality is important because EUDR compliance depends on accurate and reliable farm plot data. Issues such as incorrect geolocations, invalid geometries, topological errors, or implausible plot boundaries can affect the test results and reduce confidence in the assessment.
By reviewing the Results dashboard, Table view, Map view, and Farm plots page, users can identify which issues affect the dataset, which farm plots require attention, and what follow-up actions may be needed. Users can also use Info & Resolutions to understand the test logic and recommended next steps.
Conclusion
Understanding and interpreting test results is essential for maintaining reliable datasets and supporting EUDR compliance workflows. By reviewing the Results dashboard, checking applied tests, using the Table and Map views, and exploring farm plots through custom queries, users can identify key risks more clearly and prioritise the right follow-up actions.
These tools help users move from general risk overview to farm plot-level investigation. This makes it easier to assess whether issues require further evidence, reclassification, field verification, correction, or other resolution steps before moving forward with compliance-related decisions