GEOSPATIAL SEMANTICS -- PROBLEMS AND PROJECTS

MOTIVATION LINKING GEO-DATA GEO-ONTOLOGIES NEOGEOGRAPHY QUESTIONS

GEOSPATIAL SEMANTICS

PROBLEMS AND PROJECTS

Krzysztof JanowiczGeoVISTA 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-referencedInterconnectedMulti-thematicMulti-perspectiveMulti-dimensional

Knowledge engine



INTRODUCTION

GEO-DATA AND SERVICES



INTRODUCTION

LINKING DATA

Data SilosWeb servicesDatabasesWeb pages

hinder ad-hoc combinationenforce data modelslimit re-usability



INTRODUCTION

FROM LINKED DOCUMENTS TO LINKED DATA

Use Uniform Resource Identifiers (URI) to identify entities, link them to otherentities, encode information about these entities using themachine-understandable RDF, and make them available on the Web.



INTRODUCTION

LINKED DATA FOR SANTA BARBARA

Browsing information related to Santa Barbara using the LinkedData 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 discoveringappropriate 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 beannotated 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 cracksof more than 30mm depth [North East Somerset, UK]with a width of a ’large dinner plate’ (300mm) and the depth ofa ’golf ball’ (40mm) [Gloucestershire, UK]with a width of a ’dinner plate’ (200mm) and a minimum depth ofa ’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 restrictiveontologies exclude multi-perspective and local definitions.



PROJECT – MICROTHEORIES

PROJECT – HANDLING SEMANTIC HETEROGENEITY BYMICROTHEORIES

Employ space and time as fundamental structuring principles for thedevelopment 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 orstream.’

� 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 Spainare administrativelycontained in Europe.Hence, the Europeandefinition has to satisfythe local definitions.

Least Common Subsumer (LCS) reasoning to compute a common EUdefinition. Similarity reasoning to ensure that the result does not end upas 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 asituation more complicated as multiple sources can provide conflictingversions of the built and natural environments." (Zook et al; 2010)

"[...] an important item [...] is the formalization of rules that permitcontributed geographic information to be assessed against itsgeographic context, and [...] tools that would implement these rules."(Goodchild and Glennon; 2010)



INTRODUCTION

LINKEDGEODATA SCHOOLS IN SANTA BARBARA

School 6≡ 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-upontology personalizationby Semantic Signatures




INTRODUCING SEMANTIC SIGNATURES

Figures by ASTER Spectral Library at http://speclib.jpl.nasa.gov

Combine numerical (statistical) models and data withontologies to derive local (personal) primitives (reifications).Analogy to Spectral Signatures used in Remote SensingMultiple bands→ multiple Semantic Signatures




SEMANTIC SIGNATURES – LOCATION-BASED SOCIAL NETWORKS

Locations types and log-in patterns from Whrrl, New York, USALocal Reifications: e.g., Weekend and EveningUsed 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-occurwithin a specific semantic and spatial range.User support: generate recommendations, and clean up data basedon type likelihood. ’How likely is a recycling center directly next to anexisting one?’



THANKS, QUESTIONS?

THANKS, QUESTIONS?



THANKS, QUESTIONS?

SOCIAL IMPLICATIONS OF SEMANTIC TECHNOLOGIES

Different conceptualizations of geographic space may lead toconflicts. Can we use semantic technologies such as similarityreasoning to make the hidden differences explicit and guide thenegotiation process.



THANKS, QUESTIONS?

THANKS TO...

[I am very thankful to the contributors of Wikimedia Commons where the potholepictures were taken from. The icons and clip-arts are based on images fromOpenClipArt.org. The LOD diagram was designed by Richard Cyganiak. The collage ofrivers, forests, and estuaries has been composed by my former student StephanieDuce. The Dzero plots and the Whrll log-in figures have been created by my studentsChristoph Mülligann and Mao Ye.]


Technology

GEOSPATIAL SEMANTICS -- PROBLEMS AND PROJECTS