1. Human-Aware Sensor Networks Ontology (HASNet-O): PROV-O/OBOE/VSTO Alignments Paulo Pinheiro

2. Lake George, NY Establish a strategic partnership that becomes the global model for sustained ecosystem understanding and protection

3. 3 The Jefferson Project at Lake George: Science to Inform Solutions Smart Lake: Integrative Approach to Understanding Lake Stressors and Predicting Future Outcomes Science-based Solutions: Leveraging deep understanding for solutions with staying power for a healthy Lake George for future generations informs Cyberinfrastructure/Data Platform/Viz Lab Semantic Data Model

4. 4 We Have Completed Initial Sensor Deployment Locations and Phasing

5. 5 Sensor Deployment Phasing NB: associated deployment and maintenance resources are are not captured in this table.

6. 6 Software Architecture RPI management of production quality assets, consuming Deep Thunder data as a service

7. Sensor Network Knowledge Sensor data provide a mean for humans to understand characteristics of physical entities Most knowledge about sensor networks cannot be inferred from sensor data themselves. Moreover, the lack of contextual knowledge about sensor data can render them useless. For example, one can only understand sensor data if one minimally knows the following: – what are the physical entity characteristics being measured – how these characteristics relate to data values and measurement units

8. Selected Ontologies Provenance Knowledge – When a sensor network changes, how those changes occur? How machines can be aware of changes when changes are occurring on themselves? Sensor Infrastructure Knowledge – How can machines learn about the infrastructure of a sensor network, and the impact of the infrastructure on measurements? Measurements Knowledge – How can machines learn about the meaning of measurements in terms of physical entities, their characteristics, and the units used to quantify these measurements?

9. PROV-O Concepts

10. OBOE Concepts

11. VSTO Concepts Platform Deployment Instrument Detector Parameter Dataset hasDeployment hasInstrument hasDetector hasMeasured Parameter hasContained Parameter isFromInstrument

12. Alignments – VSTO and OBOE vsto:Platform vsto:Deployment vsto:Instrument vsto:Detector vsto:Parameter vsto:Dataset hasDeployment hasInstrument hasDetector hasMeasured Characteristic hasContained Parameter isFromInstrument oboe:Characteristic Oboe:Observation hasContained Observation

13. Alignments – PROV-O and OBOE provo:Activity oboe:Observation isA

14. Alignments – VSTO and PROV-O provo:Entity provo:Agent vsto:Dataset vsto:Instrument (or InstrumentOperatingMode) isA isFromInstrument (or isFromInstrumentOperatingMode) Was Attributed To provo:Software Agent provo:Person isA vsto:Deployment Provo:Activity isA Was Generated By Used

15. HIO Additions provo:Entity provo:Agent ConfigurationFile Configurator isA Provo:Person isA Was Attributed To Provo:Software Agent isA Sensor Configuration Skill

16. Alignments & Additions Summary provo:Entity provo:Agent vsto:Dataset vsto:Instrument isA wasAttributeTo provo:Activity oboe:Obser vation isA oboe:Characteristic oboe:Measurement hasMeasurement wasGeneratedBy wasAssociatedWith used Configuration File isA vsto:Deploym ent isA provo:Person isA Configurator hasInstrument isA ofCharacteristic contains Observation

17. Deployment (the state of being deployed) Key Sensor Lifecycle (State Diagram) Not Deployed Obsertavion (the state of observing) Idle Redeployment Deployment: activity moving a sensor from ‘not deployed’ to ‘deployed’ or from ‘deployed’ to ‘deployed’ (redeployment). Observation: activity of being in the ‘Observing’ state Deployment’s startedAtTime Deployment’s endedAtTime