AIST Program Sensor Web Meeting Summary of Results Working Group Middleware II Phil Paulsen April 3, 2008

2 Sensor Web Meeting, Working Group Middleware II Use Case Brainstorming Summary 1)Coastal Ocean Modeling, Data Assimilation and Prediction (Yi Chao) 2)Dynamic Soil Sampling (Wei Ye) 3)Dynamic Plant Monitoring (Wei Ye) 4)Water Quality Monitoring (Wei Ye) 5)Lightning (Prasanta Bose) 6)Wildfire Sensor Web (Dan Mandl) 7)Seamlessly Download Data (Mohammed Atiquzzaman) 8)Dynamically taskable sensors (Phil Paulsen) 9)Operationally Responsive Space Element Tasking (Phil Paulsen) 10)Collaborative Science Resource Allocation (Phil Paulsen) 11)North American Net Primary Production comparison using automated workflow generation (Robert Morris) 12)Data Mining and Automated Planning for Mobile Instrument Operation (Nikunj Oza) 13)Hurricane Workflows (Stuart Frye)

April 3, Sensor Web Meeting, Working Group Middleware II Fire Workflow Primary Use Case Overview Workflows, Dan Mandl, Sensor Coordination Abstract steps needed to produce final data product from an ad hoc set of sensors –Discovery –Instantiation of model –Workflow specification and generation –Workflow execution Summary –Graphical composition of of reusable workflow elements (mashups) Highlights –Hides details of manipulating sensor web for user –Reduces entry barrier making is more accessible –Increases efficiency and reduces cost –Increases science value

April 3, Sensor Web Meeting, Working Group Middleware II Workflows Mandl/Frye

April 3, Sensor Web Meeting, Working Group Middleware II Workflow Use Case: Automated Product Generation Emergency Discover available sensor assets over Internet Wizard assembles possible workflows Workflow engine controls creation of multi-sensor products, processing and delivery to user desktop Geo-Emergency First responder Theme Based Tasking Request Theme: Loc: Priority: Witch Fire (SoCal) Oct 23, 2007 Result: Efficient / timely use of assets Wizard Workflow Engine

April 3, Sensor Web Meeting, Working Group Middleware II 6 Sensor Planning Service (SPS) EO-1 Satellite Sensor Observation Service (SOS) Cappelaere/Vightel Level 0 Science Process Tran, Chien/JPL Alexander/GSFC Tran, Chien/JPL Web Processing Service (WPS) Tran, Chien/JPL Level 1G or Level 0.5 Pixels and heat values Web Coverage Service –Transformation (WCS-T) JPEG Zhao/GMU Community Map Builder client (on eo1.geobliki.com) Web Map Service (WMS) JPEG Map Publish composite JPEG map with data overlay (map with fire locations) Cappelaere/Vightel EO-1 Fire Sensor Web Workflow Potential savings –Originally, USGS charged $2000 to task EO-1 and perform L0 and L1G data processing for customers ($1250 now) –Potential cost reduced to under $100 since tasking EO-1, L0 and L1G data processing automated Cappelaere/Vightel Level 1G Process Classify hot pixels Level 0.5 Process L. Di, Zhao/GMU BPEL Workflow Engine

April 3, Sensor Web Meeting, Working Group Middleware II Asynchronous Communication A WfCS Implementation WfCS Atom Publication Message (Entry) Clearwater 1.0 Murkywater 1.0 Muddywater Workflows are uploaded and stored in WfCS database 2.Workflows are versioned automatically and assigned Definition numbers 3.An Atom/XML message is sent to the WfCS with the appropriate parameters to execute the corresponding Workflow/Definition 4.Asynchronous messaging can occur while a workflow is being executed, providing current status 5.A notification message can be sent upon completion Near Immediate Response with Process ID URL HTTP GET to Process URL Returns current status Workflow Database Process 1 Process 2 … Process N Process 1 Process 2 … Process N User/ Other Service Workflow = SensorML Process Chain

April 3, Sensor Web Meeting, Working Group Middleware II 8 Coastal Ocean Use Case Overview Name, POC: Coastal Ocean Modelling, Data Assimilation and Prediction, Payman Arabshahi Goal: To improve ocean modeling in coastal regions by making sustained measurements with increased accuracy and spatial/temporal resolution. Summary: Provide ocean and climate change scientists with improved climate change model outputs (ROMS outputs) by including integrated in-situ and space based sensor data, thus increasing accuracy and spatial/temporal resolution of model outputs. Highlights: future contributions to Earth science –JASON-1 - measures the ocean surface topography (current) –QuickSCAT - measures wind speed and direction information over oceans (current) Part of AIST demonstration –OSTM - measures sea surface height (future) –Aquarius - measures global sea surface salinity (future) Missions in NRC Decadal Survey in the time frame –SWOT- Measures ocean, lake and river water levels - Ka band wide swath radar, C band radar –XOVWM - measures sea surface wind vectors for weather and ocean ecosystems Predictive Models Virtual Space Supercomputing Sensor Web System Space, In-Situ (Oceans ) Data Assimilation Adaptive Sampling

April 3, Sensor Web Meeting, Working Group Middleware II Ocean Arabshahi

April 3, Sensor Web Meeting, Working Group Middleware II Plant Monitoring Use Case Overview Multimodal Plant Monitoring –POC: Wei Ye, Categorization: sensor management Goal: –Multimodal sensing of plants bloom in response to precipitation. Summary –Capture the dynamic response of plants to rainfalls Sap flow sensors, imaging sensor, weather station –Dynamically adjust sampling rates of sensors when relevant environmental events are detected Day time (regular rates) and night time (power down), detected precipitation (high rates) Highlights –Event-triggered reconfiguration of in-situ environmental sensors

April 3, Sensor Web Meeting, Working Group Middleware II Wei Ye Plant Monitoring

April 3, Sensor Web Meeting, Working Group Middleware II Use Case Lessons Learned Identify “collective results” of looking at several use case –Communications system management –Sensor management –Work flow management Implications for next steps –The majority of the cases related to workflow management – this area appears to be offer more opportunity for development Suggestions on how to promote use cases –Use the “value chain” analysis (more science? Better science? Cheaper science?) –Emphasis on simplification through abstraction… –Use animation / DVD –Live demonstration Provide feedback to ESTO AIST team –The use case work should not wait another year – this should be an ongoing area of interest

April 3, Sensor Web Meeting, Working Group Middleware II New Sensor Web Features, Needs Identify new features or benefits –Inclusion of a broader discussion of interoperability List any new AIST needs

April 3, Sensor Web Meeting, Working Group Middleware II Recommendations Suggestions for ESTO next steps –Continue to refine use cases Closer look at decadal survey relevance –Perform value chain analysis –Perform mashups of cross cutting use cases Crosscutting PI teams Identify specific individuals for sensor web follow up How can AIST or info systems in general, influence planning for Decadal Survey missions –Bring John Garstka to the “big” meeting with the HQ mission managers