From c50e90019f84d79f0aaac8a4b981d842a0101815 Mon Sep 17 00:00:00 2001
From: Oumaima AMAL <oumaima.amal@irit.fr>
Date: Thu, 29 May 2025 09:16:28 +0000
Subject: [PATCH] Edit README.md
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## 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.
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