diff --git a/README.md b/README.md
index 196e4b4d2e1b729524b31f85a7a282164ea0a137..6bdb593a89c64b9adb9e318d979176ce2f0c0715 100644
--- a/README.md
+++ b/README.md
@@ -2,6 +2,7 @@
 
 ## Table of Contents
 1. [About the Ontology](#about-the-ontology)
+   - [Competency questions](#competencyquestions)
    - [Overview](#overview)
    - [Ontology Classes](#ontology-classes)
    - [Object Properties](#object-properties)
@@ -13,6 +14,29 @@
 
 ## About the ontology
 
+
+### Competency Questions 
+
+This work primarily aims to propose a generic and reusable approach for data
+quality evaluation, which is a key aspect of data management. To this end, we
+extend the DQV ontology by introducing additional concepts that allow for a
+more structured and traceable management of quality assessments. To better
+clarify the objectives and expected capabilities of the proposed DQA extension,
+we define the following competency questions:
+
+- Which quality assessment processes have been performed on a specific ob-
+servation or a set of observations ?
+- What assessment method (formula-based or source-based) has been applied
+in a given quality assessment process?
+- What is the granularity level (Unique Observation or Set of Observations)
+associated with a specific assessment process ?
+- Which specific quality indicator (e.g., accuracy, timeliness, completeness)
+was assessed by a given process ?
+- What is the measured value and the assigned label resulting from an assess-
+ment process ?
+- Which data sources were identified or retrieved by source-based assessment
+methods ?
+
 ### Overview
 
 The **Data Quality Assessment Ontology (DQA)** is a suggested extension of the [Data Quality Vocabulary (DQV)](https://www.w3.org/ns/dqv#) designed to enhance the assessment of data quality (DQ). It introduces structured evaluation processes, traceability of applied methods, granularities for assessments, and results of applying DQ indicators.