INSPIRE Knowledge Base

Data Harmonisation


Data harmonisation is a key process in the development of spatial data infrastructures. Its aim is to transform different data sets in such a way that they fit together, both with respect to geometry and semantics. The goal is that a user, who is using data from different authorities, shall have a unified view, where conflicts and tensions in the data sets have been removed. The module describes the basic concepts of data harmonisation with respect to data modelling and data conversion. Special attention is paid to schema translations and the data harmonisation components according to the INSPIRE Generic Conceptual Model. The training material is mainly provided as presentations with voice and reading instructions of open resources. The module is a self-learning module.


The module consists of three parts as follows:

  • Part 1: Introduction to data harmonisation
  • Part 2: Basic Operations of data harmonisation
  • Part 3: Schema matching and mapping
Learning outcomes: 

When completing this module, the learner is expected to be able to define and describe the basic concepts of data harmonisation and schema translation.

Intended Audience: 

Professionals without experience in harmonising geographical data.


When entering this training module, we assume basic knowledge in XML, GML, UML, GI processing and data modelling.

Training format: 

PDF documents, presentations with voice, reading instructions of open resources, self-test. The module is a self-learning module.

Expected Workload: 
8 hours

Earlier versions of this training module have been developed within EuroSDR Educational Services (EduServ) in 2009 ( and the Humboldt project ( in 2010.


Author: Anders Östman, Novogit AB. The material is provided under Creative Commons Attribution Share-Alike License (

1. Context knowledge for INSPIRE