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Applying Data Quality Indicators (DQIs)

Use this guide to assess the quality and reliability of your input data across five key categories in XYCLE.

Data quality indicators (DQIs) are a critical part of Life Cycle Assessment (LCA) best practices. They help quantify the reliability, representativeness, and completeness of each data point used in your model. By assigning DQIs, you can surface uncertainty in your results, improve transparency for stakeholders, and identify which parts of your model may require better inputs in the future.

In XYCLE, DQIs are built directly into the system and can be applied to any process or inventory item. This guide walks you through how to apply them step by step.

1. Open Your LCA Model

Navigate to your existing LCA model within XYCLE. You’ll see a table of inventory items under the Unit Process section. Each row has a column titled Data Quality with a View button.

DQI Part 1

2. Open the Data Quality Menu for an Item

Click the View button in the Data Quality column for any row. This opens the DQI selection interface where you can define the quality of that data point.

DQI Part 2-1

3. Assign Each Data Quality Indicator

You'll now assign ratings across multiple dimensions:

  • Technological Representativeness – Does the data reflect the actual tech/process?

  • Geographical Representativeness – Does the data match the right region?

  • Time Representativeness – Is the data recent or outdated?

  • Completeness – Are the flows and impacts covered comprehensively?

  • Precision/Uncertainty – How reliable is the original data source?

Hover over the ℹ️ for each category to see EF Rating Criteria:

DQI 3

Use the buttons next to each dimension to select a score from 1 (excellent) to 5 (poor), based on your confidence.