My presentation at Metadata and Semantics Research Conference (MTSR 2012) 28-30 Nov 2012. Cádiz. Spain

1. Semantic Geodemography and
Urban Interoperability
J. Borrego-Díaz, A. Chávez-González,
M. Martín-Pérez and J. Zamora- Aguilera
Dept. Computer Science and Artificial Intelligence
University of Seville
6th Metadata and Semantics Research Conference MTSR 2012

2. Overview
• Introduction
• Semantic Web and (Urban) Ciberinfrastructure
• Geodemographies as knowledge augmented
spaces
• Semantizing geodemographies
• Case study
• Applications of semantic geodemography
• Conclusions and related work
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3. Data Sources
Sensors
City
National Commercial
Databases
Census Social and
demographic
surveys
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4. Data Integration
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5. Socio-Technical Systems
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6. Urban Computing & GIS
SEMANTIC
INTEROPERABILITY
http://www.westfield.ma.edu/ http://www.spaceandculture.org/2009/05/13/models-of-urban-computing/
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7. Smart City Projects
TAYLORED SERVICES
AND PROCESSES
http://www.urenio.org/category/digital-cities/page/3/
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8. Semantic Interoperability
• Services and processes
• Management and valuation of socio-
economical consequences of regions
• New methodologies: opportunities
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9. SW & GCI
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10. Geodemography
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11. MTSR 2012

12. Semantizing geodemographies
• Support for metadata
• To enhance information from sensors
• Information about geodemographic indices
• Decisions which influence city behavior
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13. Ontologies
• Step 1
– Reflecting and standarizing available information
for building systems (GCI)
– They provide us with spatial and digital knowledge
• Step 2
– High level of information fusion (future social
changes)
– Knowlege about and for urban systems
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14. Extracting an ontology
Geodemographic systems:
– Datasets apt to be statistically treated
– Systems to be interpreted by expert scientists
– Semiformal representation of a geodemographic
conceptualization
Building an ontology:
Case study. MOSAIC
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15. MOSAIC: Segmentation System
http://www.experian.co.uk/
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16. MOSAIC (by Experian Group)
• Comprises a range of segmentation systems
• Statistical techniques of classification, GIS and
software for database management
• Groups: demographic and socio-economical
features (age, ethnicity, affluence,
accommodation, etc.)
• Segmentation of consumers: prospective,
recruitment, loyalty
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17. • Detailed descriptions of a range of
sociodemographic environments
• From the ontological point of view, ideal types
• Explained by estatistical data
• Expert scientists interpret data but do not
characterize each class
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18. Limitations
• MOSAIC definitions present difficulties to be
translated into metadata
– Variance across individuals
– Variance of requirements for belonging
– Lack of critical requirements (features not included in
definitions because of sufficent statistical data have not been
provided). Examples: urban /rural nedighborhoods, tax rates, size of
houses, etc.
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19. • MOSAIC definition make use of properties
– Experts interpret but there are no data
• Class is not fully defined by Data
– Axioms can not be expressed
• Object Properties vs Data Properties
• MOSAIC definitions vs MOSAIC Data
– Weakening definitions: set of constrains
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20. O63 Group Description: Successful city dwellers owning or renting expensive
flats in trendy inner urban locations
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21. Methodology
1. Analysis of geodemographic system
– Types
– Data
– Expert’s interpretation
2. Interpretation
– Tipes as classes
– Data as (object or data) properties on classes
– Interpretation of segmentation
3. Ontology engineering
– Hierarchy construction
– Axiomatization of classes by means the characterization of properties
– Interpretation of segmentation expressed by axioms
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23. MTSR 2012

24. Applications of SG
• Geodemographic Ontology -> Social Knowledge
– Influence all the processes of informational collect, interpretation and
feedback
– Urban Informatics scope and city management
– Specialiced decisions and applications
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25. • Life cycle of knowledge in Smart Cities
• Acquisition
• Verification
• Documentation
• Decision
• Enriched not only by Sociodemographic
ontologies
• Reasoning on processed knowledge
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26. Innovation Lines on Smart city features:
• Urban planning/landscape systems (decision urban
interventions)
• Knowledge-based market for social products and
services
• Analysis of digital information increases urban
resilience
• Developing social or community apps
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27. Conclusions
• Main lines of geodemographic ontology
design and engineering
• Limitations for developing geodemographic
systems from KE
• Ontologies provide GCI with Knowledge
• Metadata enrich urban subsystems
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28. • Subsystems of an urban system
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29. • Properties of MOSAIC semantization linked to the
modelization of some urban subsystems
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30. Related works
Interrelate social and physical structures in cities/regions
• Geodemographic ontologies aligned with semantic tools like the Semantic
Framework of the Universal Ontology of Geographical Space (UOGS)
• Qualitative Spatial Reasoning applied to geodemographic zones (variograms
for binary similarities)
• TOWNTOLOGY PROJECT: Ontologies for urban civil engineering (Estimate the
impact of urban intervention on the community)
• CAMEO, OAC, ACORN, CLOUD CLIENT can be semantized. Interoperability .
• Ontology Revision : Static Geodemography / Urban Dynamics
• Desing of Intelligent interfaces for ontology repairing
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31. Thanks!
tchavez@us.es
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32. Semantic Geodemography and
Urban Interoperability
J. Borrego-Díaz, A. Chávez-González,
M. Martín-Pérez and J. Zamora- Aguilera
6th Metadata and Semantics Research Conference MTSR 2012