1. Event dashboard: Capturing user-defined semantics for event detection over real-time sensor data CSIRO LAND AND WATER Jonathan Yu | Research engineer Environmental Information Systems, CLW Highett 22 October 2013

2. 1.Background: Event detection over real-time sensor data 2.Capturing machine readable semantics – ontologies 3.Event dashboard: Capturing user-defined semantics Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 2 | Outline

3. 1.Background: Event detection over real-time sensor data 2.Capturing machine readable semantics – ontologies 3.Event dashboard: Capturing user-defined semantics Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 3 | Outline

4. Performing event detection over real-time sensor data Real-time observations are increasingly becoming available through sensor networks Reporting, monitoring, analysis Examine events that happen in a sensor network and get notifications Mitigate risk in the environment Improve management response times Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 4 | WQWeatherFlow Sensor Network

5. 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 Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 5 |

6. Sensor middleware - Global Sensor Network (GSN) Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu WQWeatherFlow Sensor Network GSN Virtual Sensor (WQ) Virtual Sensor (Flow) Virtual Sensor (Aggr.) End users User Interface 6 |

7. 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 Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 7 | Curation of event def. Coding Analysis, Monitoring, Management Sensor Middleware Sensor Network End users Programmers

8. 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 Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 8 |

9. 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 Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 9 | Sensor Middleware Sensor Network End users ?

10. 1.Background: Event detection over real-time sensor data 2.Capturing machine readable semantics – ontologies 3.Event dashboard: Capturing user-defined semantics Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 10 | Outline

11. Enable capture and consistent use of semantics Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 11 | Observation event at Flow Sensor X Observation event at Flow Sensor X Flow PVC Pipe at George Street 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 implements observes Has observation property Has feature of interest Observation event at WQ sensor Chaffey Dam Another result 10mg/L WQ meter Dissolved oxygen sensing Dissolved oxygen conc. Observation Feature of interest Sensor Output Observation Value Sensor Sensing Property

12. Users creating semantic descriptions... Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 12 | Sensor Network End users Ontologies Sensor Ontology Domain Ontology ? ? ? Event Ontology

13. 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 Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 13 | Sensor Middleware Sensor Network End users Ontology-enabled User Interface Ontologies Sensor Ontology Domain Ontology Annotates available sensors and their capabilities e.g. WQ sensor data at Location X Generate code for event detection using event constraint semantics e.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

14. Semantic Sensor Network Event- detection WQ domain WQ user Middle ontologies Application ontologies Domain ontologies User ontologies Representing domains and applications ??? 14 | Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu

15. Define events using OWL 2: Event Rule, Value Constraints Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 15 |

16. Event rule definition instances Rule IDObserved property Value constraint Feature of interest Observed By (Sensor) 1Total N. 2 > 10 mg/l 3Total N.> 10 mg/lChaffey 4Total N.> 10 mg/lWQ Sensor 1 5Total N.> 10 mg/lChaffeyWQ Sensor 2 16 | Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu

17. 1.Background: Event detection over real-time sensor data 2.Capturing machine readable semantics – ontologies 3.Event dashboard: Capturing user-defined semantics Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 17 | Outline

18. Event dashboard - User interface demo Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 18 |

19. Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 19 |

20. Ontology APIs Ontology-driven user interface Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 20 | Sensor Middleware (GSN) Event dashboard Triple store (per user definitions) Ontology Reasoner Ontology definitions End users Query/Rule engines Presentation Widgets (Standard web UIs using GWT) ESPER SNEE SOS C-SPARQL/ SparqlStream

21. Discussion Event 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) Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 21 |

22. Future work More complex events Integrate with other event ontologies Event-F Event processing ODP Incorporate processing-filters User studies to evaluate the user interface Deployments on actual sensor networks Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 22 | A B Event Smoothing function Ontology-enabled User Interface Sensor Network

23. 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 Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 23 |

24. Questions? Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 24 |

25. Land and Water Scott Gould Research Projects Officer t +61 3 9252 6103 escott.gould@csiro.au wwww.csiro.au/clw ICT Centre Kerry Taylor Principal Research Scientist t+61 2 6216 7038 ekerry.taylor@csiro.au wwww.csiro.au/ict Land and Water Donavan Marney Research team leader t +61 3 9252 6585 edonavan.marney@csiro.au wwww.csiro.au/clw LAND AND WATER Thank you Land and Water Jonathan Yu Research Software Engineer t+61 3 9252 6440 ejonathan.yu@csiro.au wwww.csiro.au/clw Land and Water Paul Davis Research Scientist t +61 3 9252 6310 epaul.davis@csiro.au wwww.csiro.au/clw Land and Water Brad Sherman Research Scientist e Brad.Sherman@csiro.au wwww.csiro.au/clw

26. Event dashboard - User interface demo Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu 26 |