GEOSPATIAL SEMANTICS -- PROBLEMS AND PROJECTS

MOTIVATION LINKING GEO-DATA GEO-ONTOLOGIES NEOGEOGRAPHY QUESTIONS
GEOSPATIAL SEMANTICS
PROBLEMS AND PROJECTS
Krzysztof Janowicz
GeoVISTA Center, Pennsylvania State University, USA
March 10, 2011
GEOSPATIAL SEMANTICS – PROBLEMS AND PROJECTS KRZYSZTOF JANOWICZ

RETRIEVAL AND INTEGRATION
RESEARCH STREAMS ANALOGY

RETRIEVAL AND INTEGRATION
DIGITAL EARTH – RETRIEVAL AND INTEGRATION
Digital Earth
Geo-referenced
Interconnected
Multi-thematic
Multi-perspective
Multi-dimensional
Knowledge engine

INTRODUCTION
GEO-DATA AND SERVICES

INTRODUCTION
LINKING DATA
Data Silos
Web services
Databases
Web pages
hinder ad-hoc combination
enforce data models
limit re-usability

INTRODUCTION
FROM LINKED DOCUMENTS TO LINKED DATA
Use Uniform Resource Identiﬁers (URI) to identify entities, link them to other
entities, encode information about these entities using the
machine-understandable RDF, and make them available on the Web.

INTRODUCTION
LINKED DATA FOR SANTA BARBARA
Browsing information related to Santa Barbara using the Linked
Data version of Wikipedia (DBpedia).

INTRODUCTION
LINKED DATA – CREATING THE GLOBAL GRAPH
Integration by searching equivalent types or same features in data sets.

PROBLEM – MOST GEO-DATA IS NOT ACCESSIBLE
PROBLEM – MOST GEO-DATA IS NOT ACCESSIBLE

PROJECT – TRANSPARENT SEMANTIC ENABLEMENT
Connect both worlds without changing any standards
Encapsulate SW technologies by OGC Web Processing Services (WPS)
Encapsulate OGC services using RESTful proxies (e.g., RESTful SOS)

USING SEMANTIC WEB REASONING FOR SENSOR DISCOVERY
Ontologies and Semantic Web technologies can assist in discovering
appropriate geo-sensors and observation data (Sensor Plug & Play).

SEMANTIC SENSOR WEB ONTOLOGIES
W3C XG SSN STIMULUS SENSOR OBSERVATION PATTERN
For semantic integration and retrieval, Linked Data needs to be
annotated with ontologies that describe the meaning of the used terms.

INTRODUCTION
GEO-ONTOLOGIES AND HETEROGENEITY

INTRODUCTION
ONTOLOGY – RESTRICTING INTERPRETATIONS
STRUCTURE MATTERS

INTRODUCTION
LOCATION MATTERS

INTRODUCTION
TIME MATTERS

INTRODUCTION
SOCIAL STRUCTURE MATTERS

INTRODUCTION
AN ONTOLOGY OF POTHOLES
Potholes are deﬁned as cracks
of more than 30mm depth [North East Somerset, UK]
with a width of a ’large dinner plate’ (300mm) and the depth of
a ’golf ball’ (40mm) [Gloucestershire, UK]
with a width of a ’dinner plate’ (200mm) and a minimum depth of
a ’ﬁst’ (40mm) [Worcestershire, UK]
if their depth is ’a pound coin and a 1p coin side by side’
[Coventry]
=⇒
Due to a severe winter (T) millions of potholes need to be repaired
by the local councils (S) that are legally responsible for the roads
maintenance (A) within their administrative boundaries (S) .

INTRODUCTION
ONTOLOGIES CANNOT FIX MEANING
ACCORDING TO OUR ONTOLOGY THIS IS A POTHOLE

INTRODUCTION
ONTOLOGIES CANNOT FIX MEANING
REASONING: CONSTRUCTING BRIDGES CREATES POTHOLES

PROBLEM – INTEROPERABILITY VS. HETEROGENEITY
PROBLEM – INTEROPERABILITY VS. HETEROGENEITY
Too generic ontologies fail to restrict meaning; too restrictive
ontologies exclude multi-perspective and local deﬁnitions.

PROJECT – MICROTHEORIES
PROJECT – HANDLING SEMANTIC HETEROGENEITY BY
MICROTHEORIES
Employ space and time as fundamental structuring principles for the
development of ontologies.
Similar to Couclelis’ semantic contraction (without pre-deﬁned levels).

INSPIRE EXAMPLE– COMPUTING A COMMON GROUND
INSPIRE Watercourse: ’A natural or man-made flowing water course or
stream.’
Instead of a top-down ontology for the EU that violates local definitions,
compute a top-level based on local definitions of the member states.
*)INSPIRE: Infrastructure for Spatial Information in the European Community

INSPIRE EXAMPLE– LCS AND SIMILARITY
Germany and Spain
are administratively
contained in Europe.
Hence, the European
definition has to satisfy
the local definitions.
Least Common Subsumer (LCS) reasoning to compute a common EU
definition. Similarity reasoning to ensure that the result does not end up
as the compromise of nobody.

PRESERVING LOCAL CONCEPTUALIZATIONS
The INSPIRE deﬁnition is too restrictive

INTRODUCTION
INCORPORATING VGI

INTRODUCTION
SANTA BARBARA IN VGI
"[Various VGI sources and duplication] make [the] interpretation of a
situation more complicated as multiple sources can provide conﬂicting
versions of the built and natural environments." (Zook et al; 2010)
"[...] an important item [...] is the formalization of rules that permit
contributed geographic information to be assessed against its
geographic context, and [...] tools that would implement these rules."
(Goodchild and Glennon; 2010)

INTRODUCTION
LINKEDGEODATA SCHOOLS IN SANTA BARBARA
School ≡ University; ∃x(School(x) ∧ ¬ManMade(x))

INTRODUCTION
LINKEDGEODATA SCHOOLS IN NEW YORK
∃x(School(x) ∧ University(x))?

INTRODUCTION
WIKIMAPIA SCHOOLS IN SANTA BARBARA
∃x(School(x) ∧ University(x)); ∃x(University(x) ∧ NightClub(x))

PROBLEM – INTEGRATION BY CLASS EQUIVALENCE
PROBLEM – INTEGRATION BY CLASS EQUIVALENCE
LGDSB : School ≡ LGDNY : School ≡ WikimapiaSB : School?

PROJECT – SEMANTIC SIGNATURES
Bottom-up
ontology personalization
by Semantic Signatures

INTRODUCING SEMANTIC SIGNATURES
Figures by ASTER Spectral Library at http://speclib.jpl.nasa.gov
Combine numerical (statistical) models and data with
ontologies to derive local (personal) primitives (reiﬁcations).
Analogy to Spectral Signatures used in Remote Sensing
Multiple bands → multiple Semantic Signatures

SEMANTIC SIGNATURES – LOCATION-BASED SOCIAL NETWORKS
Locations types and log-in patterns from Whrrl, New York, USA
Local Reiﬁcations: e.g., Weekend and Evening
Used to automatically compute missing types of Whrrl POIs

SEMANTIC SIGNATURES – SPATIAL-SEMANTIC-PATTERNS
POIs plotted by similarity to bar and recycling in OSM data, London, UK
Reiﬁcations: e.g., Uniform and Clumped (local signatures)
Bars (and similar features) tend to clump together
Recycling (and similar features) are rather uniformly distributed

SEMANTIC SIGNATURES – SPATIAL-SEMANTIC INTERACTION
Dzero measures the likeliness of features of a certain type to co-occur
within a speciﬁc semantic and spatial range.
User support: generate recommendations, and clean up data based
on type likelihood. ’How likely is a recycling center directly next to an
existing one?’

THANKS, QUESTIONS?
THANKS, QUESTIONS?

THANKS, QUESTIONS?
SOCIAL IMPLICATIONS OF SEMANTIC TECHNOLOGIES
Different conceptualizations of geographic space may lead to
conﬂicts. Can we use semantic technologies such as similarity
reasoning to make the hidden differences explicit and guide the
negotiation process.

THANKS, QUESTIONS?
THANKS TO...
[I am very thankful to the contributors of Wikimedia Commons where the pothole
pictures were taken from. The icons and clip-arts are based on images from
OpenClipArt.org. The LOD diagram was designed by Richard Cyganiak. The collage of
rivers, forests, and estuaries has been composed by my former student Stephanie
Duce. The Dzero plots and the Whrll log-in ﬁgures have been created by my students
Christoph Mülligann and Mao Ye.]

GEOSPATIAL SEMANTICS -- PROBLEMS AND PROJECTS

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