1. Ontology as Knowledge Base
for Spatial Data Harmonization
Otakar Cerba, Karel Charvat
University of West Bohemia, Plzen, Czech Republic
Help Service Remote Sensing, Benesov, Czech Republic
26.06.2012 INSPIRE 2012 1

2. Objectives

Spatial data harmonization – basics

Domain ontology – theory & essential principles

Harmonization ontology – components

Example of harmonization based on ontology

Conclusion
26.06.2012 INSPIRE 2012 2

3. Spatial data harmonization

Activity for elimination or reduction of
heterogeneities of various properties of spatial
data to support interoperability

The elimination of the aspects of spatial data
heterogeneity cannot be based on a creation of some
uniform rules and data models, because, there are
too many subjects with individual requirements –
formats, precision, reference systems, terminology...

The harmonization processes should be divided into
small and simple substeps
26.06.2012 INSPIRE 2012 3

4. Conditions of successful harmonization

Theoretical knowledge (domain, geomatic, IT...)

Understandable user requirements

Cooperation of experts

Sequence of harmonization substeps

Multi-level data description
26.06.2012 INSPIRE 2012 4

5. Why to harmonize

To enable a sharing, combining and publishing of
data

To re-use existing sources

To improve data quality

To use web services and other automatic tools
(SaaS)

To keep data interoperability (it's cool!)
All reasons

To increase the number of stakeholders are strongly

To meet legislation requirements interconnect
ed
26.06.2012 INSPIRE 2012 5

6. Ontology – Theory

To improve communication between all participating
subjects (cartographers, users, IT experts, domain
experts...)
… exactly defined
… clearly
syntax
semantically defined
concepts ...formal and
formalized explicit … precise list of
… directly specification of terms
expressed
sharing
conceptualization
… suitable for re- … way how a human
use understands the world
26.06.2012 INSPIRE 2012 and how it expresses6

7. Ontology – Fundamental components

Class (Concept) – particular parts of domain
structured by is-a relation

Individual – particular parts of domain that cannot be
divided

Property – detail description of specifics of classes or
individuals; object & data type properties

Axiom – logical constructs between elements of
ontology (e.g. closure axiom, cover axiom)

Annotation – metadata, description, explanation
26.06.2012 INSPIRE 2012 7

8. Ontology: Classes & Properties
Classes Properties
26.06.2012 INSPIRE 2012 8

9. Role of ontology in harmonization process
Heterogeneous
Data
Data
Description
Harmonization Harmonized
Tool(s) Data
Knowledge
& Experience To
formalize
and
Rules & process
Ontology
Methods extra
26.06.2012 INSPIRE 2012 informatio 9
n

10. Data description in ontology
26.06.2012 INSPIRE 2012 10

11. Proposal of harmonization substeps
Before
After reasoning
reasoning
26.06.2012 INSPIRE 2012 11

12. Inferred Ontology – Data Description
26.06.2012 INSPIRE 2012 12

13. LU/LC Legend mapping ontology
26.06.2012 INSPIRE 2012 13

14. LU/LC Legend mapping ontology – parameters
26.06.2012 INSPIRE 2012 14

15. LU/LC Legend mapping ontology – example
Reasoning
Equivalent
classes
Inferred (new) information
Asserted (original)
26.06.2012 information INSPIRE 2012 15

16. LU/LC Legend mapping ontology
26.06.2012 INSPIRE 2012 16

17. Harmonization in ETL tool
Input file Replication Transformation Changing Outputs
(CLC)
26.06.2012 to more to new data
INSPIRE 2012 attribute (PELCOM etc.) 17
outputs models values

18. Results of LULC data harmonization
PELCOM
CLC
26.06.2012 INSPIREPELCOM
2012 18
After manual final harmonization

19. Conclusion

Harmonization is not only technical process but also
semantic...

It is necessary to consider a suitability of data sets
from the view of
− Data completeness
− Data quality (depend for purposes of result)
− Semantics of the data sets and classification
systems

Ontologies enable knowledge transfer and better
communication (including information sharing)
26.06.2012 INSPIRE 2012 19

20. Thank you for your attention
and questions
cerba@kma.zcu.cz
charvat@ccss.cz
26.06.2012 INSPIRE 2012 20