a model of events for integrating event-based information in complex socio-technical information...

A Model of Events for Integrating Event-Based Information in Complex Socio-technical Information Systems

Ansgar Scherp, Thomas Franz, Carsten Saathoff, Steffen Staab

Institute WeSTUniversity of KoblenzGermany

http://west.uni-koblenz.de/

Web Science and Technologies

Ansgar [email protected]

Event-Model-FSlide 2

Emergency Control Center

Forward Liaison Officer

Documentarysupport

Calls to report about a power outage

Creates incident with audio recording

Request to report about a flooded cellar

Reports by taking photos etc.

Emergency Response Coordination

Emergency Hotline

Fire Department

Police Department

Coordinate and keep up to

dateReport and update about the incident

Coordinate and keep up to date

Report and updateabout the incident

Citizen

Emergency Response Scenario

EU Integrated Project WeKnowIthttp://www.weknowit.eu/

• Several emergency response entities are involved • Using different event-based systems• Common understanding of exchanged multimedia

information is needed to efficiently communicate between ER entities

Snapped pole image from: http://www.dailymail.co.uk/

http://www.weknowit.eu/




Outlook

Emergency Response Scenario Motivation Formal Model of Events Existing Event Models Future Work




Motivation

Events need to be modeled and are useful in a variety of application domains Lifelogs, multimedia experience sharing Emergency response Cultural heritage News Sports Surveillance …

However Event detection and annotation from different sources Using different data models and proprietary solutions Event descriptions need to be shared between systems




Event-Model-F

• Humans like to think in terms of events & entities• Human-centered approach to capture

experience and knowledge

• Development of core ontology Event-Model-F• Sophisticated modeling support for occurrences in which

humans participate• Homage to event model E by Westermann & Jain

• Events• Occurrences in which humans participate

• Subject to interpretation and discussion




Requirements to a Common Event Model

• Participative aspect• Temporal aspect • Spatial aspect• Structural aspect

• Mereology (composition)• Causality• Correlation

• Interpretation• Experiential aspect (documentation)




7

Comparison to Existing Event Models

SsVM = Semantic-syntactic video modelVERL = Video event representation languageCIDOC CRM = Conceptual reference model for cultural heritage




Ontology Patterns of Event-Model-F

• Event-Model-F defines six core ontology patterns based on Description and Situation pattern(1) Participation pattern (2) Mereology pattern (composition)(3) Causality pattern(4) Correlation pattern(5) Documentation pattern(6) Interpretation pattern

• Specified in Web Ontology Language (OWL)• Formalized in Description Logics• Graphical representation in UML-like notation




Modeling Basis of Event-Model-F

• Ontology pattern Descriptions and Situations (DnS) as fundamental design principle for Event-Model-F

• Formal representation of context through use of roles• Decoupling concrete events and objects from their roles in a

specific contextual situation

• Description• Specification of roles required in a specific situation• Can be understood as template

• Situation• Observable real-world situation, i.e., a concrete

combination of events and objects• Satisfies a description, if it fits into the template




Example: Descriptions and Situations Pattern

• DomesticPowerOutage-Description defines roles• AffectedBuildingRole• AffectedPersonRole• …

• DomesticPowerOutage-Situation defines objects House-1 : Object

Paul-1 : Object,Sandy-1 : Object,……

• Important: Different people may claim different causes for the outage

• Different interpretations of the same DomesticPowerOutageSituation

a) Snapped power pole

b) Problem with the power plantImage source: Wikipedia

Classify




(3) Causality Pattern

• Event (cause) implies other event (effect)• Causal relationship holds under some justification• Causes and effects are events, and only events

Description

EventCausalityDescription

EventCausalitySituation

Situation

Cause Effect Justification

EventRole

Concept

Event Description

classifies isRoleOf

defines

isEventIncludedIn

satisfies

isObjectIncludedIn

Role

EventCausalityDescriptiondefines exactly 1 Causedefines exactly 1 Effectdefines exactly 1 Justificationdefines only (Cause or Effect or Justification)isSatisfiedBy exactly 1 EventCausalitySituation

Example: The event of a snapped power pole causes a power outage.




(1) Participation Pattern

• Participation of living and non-living objects in events• Reuse of domain knowledge

Roles the entities play

Real world entities

EventParticipationDescriptiondefines exactly 1 DescribedEventdefines min 1 Participantdefines some LocationParameterdefines some TimeParameterdefines only (DescribedEvent or Participant or

LocationParameter or TimeParameter)isSatisfiedBy exactly 1 EventParticipationSituation

Example: Firemen and home owner are involved in an incident of a house fire.




(2) Mereology Pattern

EventCompositionDescription

Description

Concept Parameter

EventRole

Component

EventCompositionConstraint

TemporalConstraint

SpatioTemporalConstraint

Situation

Event

Quality

Time-Intervalsatisfies

defines

classifies

parametrizes

classifies

isEventIncludedIn

isTimeIncludedIn

hasQuality

isParameterFor

SpatialConstraint

Spatio-Temporal-Region

Space-Region

parametrizes

parametrizes

Object

isSpaceTimeIncludedIn

isSpaceIncludedIn

hasParticipant

hasRegion

EventCompositionSituation

Composite

hasQuality

• Composite event consists of multiple component events• Composition along time, space, and space-time

EventCompositionDescriptiondefines exactly 1 Compositedefines min 1 Componentdefines only (Composite or Component or

EventCompositionConstraint)isSatisfiedBy exactly 1 EventCompositionSituation

Example: Events of a snapped power pole, power outage, and bursting of a dam are components of a larger flooding event.




(4) Correlation Pattern

• Correlate events have a common cause• Happen at the same time or share some overlap• Useful, as often only correlation is observable and the

common cause remains unknown

Description

EventCorrelationDescription

EventCorrelationSituation

Situation

Justification

EventRole

Concept

Event Description

classifies

defines

isEventIncludedIn

satisfies

isObjectIncludedIn

classifies

Correlate

Role

EventCorrelationDescriptiondefines min 2 Correlatedefines exactly 1 Justificationdefines only (Correlate or Justification)isSatisfiedBy exactly 1 EventCorrelationSituation

Example: Several correlating power outage events happen in the city.




(5) Documentation Pattern

• Provide documentary evidence for an event• Annotation of events with photos, video, audio, etc.

EventDocumentationDescriptiondefines exactly 1 DocumentedEventdefines some Documenterdefines only (DocumentedEvent or Documenter)isSatisfiedBy exactly 1 EventDocumentation-

Situation

Example: • Documenter classifies ImageData defined in COMM

(Core Ontology on Multimedia) • Formal model of MPEG-7 low-level descriptors




(6) Interpretation Pattern

• Explicit modeling of contextual views on events• Combines the instantiations of patterns (1) to (5)

EventInterpretationDescription

Description

EventInterpretationSituation

Role

EventRole

SituationEvent

satisfies

defines

isEventIncludedIn

RelevantSituation

Situation

classifies

RelevantComposition

RelevantCausality

RelevantParticipation

isObjectIncludedIn

classifies

Interpretant

Domain Ontology

RelevantCorrelation

EventInterpretationDescriptiondefines exactly 1 Interpretantdefines min 1 RelevantSituationdefines only (Interpretant or RelevantSituation)isSatisfiedBy exactly 1 EventInterpretationSituation

For example: Interpretation of a power outage• Citizen: power outage on our street is caused by

snapped power pole

• Officer: power outage of the city is caused by a problem in the power plant




Design Approach

1. Chose of foundational ontology DOLCE+DnS Ultralight as modeling basis

• Aims at capturing the most essential aspects in the world• Defines disjunctive upper classesEvent, Object, Quality and Abstract

• Follows a pattern-oriented approach for ontology design

2. Use of ontology design patterns • Generic solution to recurring modeling problem• Reduces complexity of the designed model

3. Defining Event-Model-F as core ontology • Provides structural knowledge that spans across multiple

domains, e.g., lifelogs, emergency response, etc.• Build on top and align it with DOLCE+DnS Ultralight




Comparison to Existing Event Models

• Event Model E, EventML, Event Calculus, CIDOC CRM, VERL, SsVM, Event Ontology, Eventory

• Do not follow such a systematic development approach• Semantically ambiguous• Conceptually narrow • Hinders interoperability of different event-based systems




SemaPlorer

19

Place ObjectType Event




20

Future work on Event-Model-F

• Extraction of events and objects from Web content• Reasoning on Event-Model-F with Linked Geo Data

• Event-Model-F Website • Provides the ontology and examples in OWL• Implementation of Java API • http://west.uni-koblenz.de/eventmodel/

http://isweb.uni-koblenz.de/eventmodel/






Thank you for your attention!

Questions?

Ansgar Scherp

[email protected]

http://west.uni-koblenz.de/

mailto:[email protected]

http://isweb.uni-koblenz.de/








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What is an event?

• Events• Perduring entities that unfold over time• Occurrences in which humans participate• Subject to discussions and interpretations by humans

• Objects• Enduring entities that unfold over space

• Events and objects require each other




Ontology Stack

Core Ontologies

Domain Ontologies

Foundational Ontologies

• Domain Ontologies• Cover a specific domain• Example: fishery, human body, emergency response, etc.

• Core Ontologies• Coverage: span across multiple domains• Examples: annotation, communication, events, ...

• Foundational Ontologies• Span across multiple core ontologies




Non-functional Requirements

• Extensibility• Include future aspects for describing events

• Axiomatization & formal precision• Required for a common understanding of events• Interoperability between systems

• Modularity• Reduce complexity by selecting only what is required

• Reusability• Share common events/objects for different interpretations• Reuse of domain knowledge

• Separation of concerns• Core model needs to be applicable in many different domains• Separate structural knowledge from domain-specific knowledge




Non-functional Requirement

• Extensibility• Pattern-oriented approach of DOLCE+DnS Ultralight• Specializing/extending existing patterns, adding new patterns, …

• Axiomatization & formal precision• Foundational ontology DOLCE+DnS Ultralight as basis• Semantically precise through Description Logics

• Modularity• Pattern-oriented design

• Reusability• Integrating existing domain ontologies

• Separation of concerns• Structural knowledge is defined in the ontology design patterns• Domain-specific knowledge is linked through classifying roles




Event-Model-F API

• Programming interface to Event-Model-F• Enable direct use of the Event-Model-F without requiring

to know the internal details of the ontology• Layered architecture of the API

Your Application

Event-Model-F Extended API

Event-Model-F Core API

RDF Storage (Sesame)

• Release under open source licensehttps://launchpad.net/eventmodelf

• Will be released under open source license (soon)

https://launchpad.net/eventmodelf




Short Example: Serious Weather Conditions

• During serious weather conditions a flood happens• Causality: power pole snappes and causes a power outage• Participation: citizen observes this event from his home

a model of events for integrating event-based information in complex socio-technical information...

Technology

modelf eventmodel

event model e

event detection

ontology patterns of

causality pattern event

existing event modelsssvm

modeling basis of event

different eventbased