Using Explicit Semantic Representations for User Programming of Sensor Devices Kerry Taylor and Patrick Penkala CSIRO ICT Centre Melbourne, 1 st December 2009 Image: Burdekin Sensor Network, Pavan Sikka & Google

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 Context lots of pics of sensors

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 SSN-XG: Semantic Sensor Network Incubator Group Commenced 1 March Two main objectives: (a) the development of ontologies for describing sensors, and (b) the extension of the Sensor Model Language (SML), one of the four SWE languages, to support semantic annotations.

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 Aim: To address real-time programming, tasking and querying sensors and sensor networks Represent the semantics of the command language in an ontology Use generic software tools, plus device-specific “transformer” and communication code modules Assume a stateless model (declarative queries) simplicity amenability to optimisation multi-user sharing (detect query subsumption, for example)

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 Case Study: an Automatic Weather Station Environdata WeatherMaster1600 sensors for: air temperature, relative humidity, wind speed, wind direction + 3 simulated sensors: voltages of the battery and solar panel and the activity of the serial port. proprietary command-line language of about 50 commands request-response interaction style over a serial port. Data is time-stamped and logged: for each of the four sensors at once. 104 kilobytes memory, FIFO

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 Environdata Command Language Main Commands: STORAGE to measure data and log in memory “STORAGE 13 CURRENT EHOUR 1 0” command 13 logs the current wind direction in memory 2 every hour. MEM to retrieve data from memory “MEM 4 SPECIFIC ” requests logged data in MEM 4 for the given 24 hour period R for current values for all sensors “R”

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December Model the Commands in an Ontology queryCurrentData queryPeriodData setStorageFunction

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December Phrase queries using ontology terms in a device- independent query tool

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December Classify query and instantiate

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December Execute and see the results!

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 Benefits Offers a device-independent route to sensor programming, but avoids standardising to lowest common model. Validates queries by classification Is self-documenting language through semantic context. Can accommodate (some) evolution without coding. Can also use the ontology modelling and DL reasoning to Represent variation in query capability amongst similar devices Allocate queries to devices that are sufficiently capable Admit alternative “syntaxes” (or terminology) for same functions Discover sensors by function, location, latency, frequency, accuracy, data format, custodian,... Optimise wrt query subsumption (e.g. logging frequency) Can extend to composition, substitution, spatial and temporal reasoning etc (see Compton et al in Proc Semantic Sensor Networks 2009)

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009 Future Work Phenomics: Start with a particular observable trait or phenotype and work back to discover the causal gene.

Contact Us Phone: or Web: Thank you CSIRO ICT Centre Kerry Taylor Research Scientist Phone: Web: SSN-XG: