This document discusses using ontologies as the basis for spatial data harmonization. It defines spatial data harmonization as the process of eliminating heterogeneities in spatial data properties to support interoperability. An ontology provides a formal representation of concepts and their relationships in a domain that can be used to describe data and map between different classifications and legends. The document proposes using an ontology to formalize the knowledge and rules for harmonizing land use/land cover data from different sources through an extraction, transformation, and loading tool.

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
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2. Objectives

Spatial data harmonization – basics

Domain ontology – theory & essential principles

Harmonization ontology – components

Example of harmonization based on ontology

Conclusion
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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
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4. Conditions of successful harmonization

Theoretical knowledge (domain, geomatic, IT...)

Understandable user requirements

Cooperation of experts

Sequence of harmonization substeps

Multi-level data description
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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
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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
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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
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8. Ontology: Classes & Properties
Classes Properties
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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
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n

10. Data description in ontology
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11. Proposal of harmonization substeps
Before
After reasoning
reasoning
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12. Inferred Ontology – Data Description
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13. LU/LC Legend mapping ontology
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14. LU/LC Legend mapping ontology – parameters
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15. LU/LC Legend mapping ontology – example
Reasoning
Equivalent
classes
Inferred (new) information
Asserted (original)
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16. LU/LC Legend mapping ontology
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17. Harmonization in ETL tool
Input file Replication Transformation Changing Outputs
(CLC)
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outputs models values

18. Results of LULC data harmonization
PELCOM
CLC
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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)
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20. Thank you for your attention
and questions
cerba@kma.zcu.cz
charvat@ccss.cz
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