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Event dashboard: Capturing user-defined semantics for event detection over real-time sensor data
CSIRO LAND AND WATER
Jonathan Yu | Research engineerEnvironmental Information Systems, CLW Highett
22 October 2013
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
1. Background: Event detection over real-time sensor data
2. Capturing machine readable semantics – ontologies
3. Event dashboard: Capturing user-defined semantics
2 |
Outline
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
1. Background: Event detection over real-time sensor data
2. Capturing machine readable semantics – ontologies
3. Event dashboard: Capturing user-defined semantics
3 |
Outline
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Water quality issues...
Example events in this domain:• Total nitrogen conc. in a river > X mg/L• Dissolved oxygen conc. at sensor < Y mg/L
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Sensor middleware - Global Sensor Network (GSN)
WQ Weather Flow
Sensor Network
GSN
Virtual Sensor (WQ)
Virtual Sensor(Flow)
Virtual Sensor (Aggr.)
End users
User Interface
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Existing workflow: real-time event detection
High level entry for an end user e.g. Scientists and managers• Inefficient
Knowledge hidden behind code or in people’s heads, i.e. implicit semantics• Barrier for reusability• Possible inconsistencies
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Curation of event def. Coding
Analysis, Monitoring,
Management
SensorMiddleware
Sensor Network
End users
Programmers
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Problem of data heterogeneity, integration
Multiple datasets, data schemas, formats, field names, conventions
The use of the observation property “Total Nitrogen”• N_TOT• Total_Nitrogen• TN
Actually want to refer to semantics, not only syntax
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Enabling users...
Enabling user-based real-time event detection
1) Sensor network system semantics (e.g. WQ sensor is located at X)
2) Domain of interest semantics (e.g. Total Nitrogen is an observable property)
3) Event semantics (e.g. Total Nitrogen at sensor#1 > 10.0 mg/L)
4) Machine-readability: for rendering in user interfaces & code generation
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SensorMiddleware
Sensor Network
End users
?
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
1. Background: Event detection over real-time sensor data
2. Capturing machine readable semantics – ontologies
3. Event dashboard: Capturing user-defined semantics
10 |
Outline
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Enable capture and consistent use of semantics
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Observation event at Flow Sensor X
Flow
PVC Pipe at George Street
100 litres per second
Flow sensor X
Flow rate sensing
Has an observation result
Some result
Has value
Produced by
implementsobserves
Has observation property
Has feature of interest
Observation event at WQ sensor
Chaffey Dam
Another result 10mg/L
WQ meter
Dissolved oxygen sensingDissolved
oxygen conc.
Observation
Feature of interest
Sensor Output Observation Value
Sensor
SensingProperty
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Users creating semantic descriptions...
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Sensor Network
End users
Ontologies
SensorOntology
DomainOntology
? ? ?
EventOntology
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Return notifications from triggered events with metadata based on ontology semantics
e.g. The Chaffey Dam has a problem due to <...>
Ontology-driven event detection system
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SensorMiddleware
Sensor Network
End users
Ontology-enabledUser Interface
Ontologies
SensorOntology
DomainOntology
Annotates available sensors and their capabilities
e.g. WQ sensor data at Location X
Generate code for event detection using event constraint semanticse.g. Total N > 10 mg/l
Populate user interface elements based on domain semantics and sensor network annotations.
Allow users to define event constraints
Event Ontology
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Semantic Sensor
Network
Event-detection
WQdomain
WQ user
Middle ontologies
Application ontologies Domain ontologies
User ontologies
Representing domains and applications
???
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Define events using OWL 2:Event Rule, Value Constraints
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Event rule definition instances
Rule ID Observed property
Value constraint
Feature of interest
Observed By (Sensor)
1 Total N.
2 Total N. > 10 mg/l
3 Total N. > 10 mg/l Chaffey
4 Total N. > 10 mg/l WQ Sensor 1
5 Total N. > 10 mg/l Chaffey WQ Sensor 2
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
1. Background: Event detection over real-time sensor data
2. Capturing machine readable semantics – ontologies
3. Event dashboard: Capturing user-defined semantics
17 |
Outline
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Event dashboard - User interface demo
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu19 |
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Ontology APIs
Ontology-driven user interface
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SensorMiddleware
(GSN)
Event dashboard
Triple store(per user definitions)
Ontology Reasoner
Ontology definitions
End usersQuery/Rule engines
Presentation Widgets(Standard web UIs
using GWT)
ESPER
SNEE
SOS
C-SPARQL/SparqlStream
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
DiscussionEvent descriptions using OWL2 vs. Rules (SWRL, SPIN, RIF)
• Event description approach allows adding/deleting Abox statements (instances)
• Event descriptions allow DL reasoning and SPARQL queries• Rules allow different kind of semantics to be captured• Rules require additional rules engine (triple store support?) • Can’t refer to rule statements via URIs/IRIs?
Generic UI vs. SSN coupled-UI• The latter allows for sensor/observation classes to be bound to UI• Reuse of UI given other domain ontologies (flash-flood detection)
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Future work
More complex eventsIntegrate with other event ontologies
Event-FEvent processing ODP
Incorporate processing-filters
User studies to evaluate the user interface
Deployments on actual sensor networks
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A
BEvent
Smoothing function
Ontology-enabledUser Interface
Sensor Network
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Summary
Availability of real-time sensor data: many potential applications
Utilise ontologies for capture machine readable event semantics – SSN, event, domain ontologies
Event dashboard• assists user-definition of events over a given sensor network• consistent use of domain, application, sensor network semantics• UI reusable for other domains and applications
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Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu
Questions?
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Land and WaterScott GouldResearch Projects Officert +61 3 9252 6103e [email protected] www.csiro.au/clw
ICT CentreKerry TaylorPrincipal Research Scientistt +61 2 6216 7038e [email protected] www.csiro.au/ict
Land and WaterDonavan MarneyResearch team leadert +61 3 9252 6585e [email protected] www.csiro.au/clw
LAND AND WATER
Thank youLand and WaterJonathan YuResearch Software Engineert +61 3 9252 6440e [email protected] www.csiro.au/clw
Land and WaterPaul DavisResearch Scientistt +61 3 9252 6310e [email protected] www.csiro.au/clw
Land and WaterBrad ShermanResearch Scientist
e [email protected] www.csiro.au/clw