1. DATAFED Application Programs

2. Dvoy Data Flow and Processes DataView 1 View Data Abstract Portrayal Device Portrayal Render Device View Portrayal Device Driver Trans - mission Abstr.Data Access View Wrapper Physical Data Abstract Data Physical Data Physical Data reside in servers Data are accessed by view-specific wrappers yielding homogeneous abstract data ‘slices’ Abstract Data Abstract Data are virtual Abstract data are requested by viewers; homogeneous real data are delivered by abstract interface DataView 2 DataView 3 View Data View Data enriched for portrayal View data from abstract interface are enriched by parameters useful for portrayal/processing

3. I/O Abstractions in The Program The Voyager program consists of a stable core and adoptive input/output section The core executes the data selection, access portrayal tasks The adoptive, abstract I/O layer connects the core to evolving web data, flexible displays and to the a configurable user interface: –Wrappers encapsulate the heterogeneous external data sources and homogenize the access –Device Drivers translate generic, abstract graphic objects to specific devices and formats –Ports expose the internal parameters of Voyager to external controls Data Sources Controls Displays Web Apps: Web services chains for: Selection, Access, Portrayal Abstract I/O Layer Wrappers Control Ports Device Drivers WSDL Ports Web Services

4. Browser Architecture (0312) View State MapView[1] Services Servicetype1[1] Servicetype2[1] Servicetype2[2] FlowProgram Controllers TimeView[1] Services FlowProgram Controllers MapView[1] TimeView [1] Controllers

5. Interpreted and Compiled Service Point Access Point Grid Grid Render Point Render PtGrid Overla y Point Access Point Grid Grid Render Point Access Point Render PtGrid Overlay Interpreted Service Processes distributed Data flow on Internet Compiled Service Processes in the same place Data flow within aggregate service Controllers, e.g. zoom can be shared Data Flow Control Flow

6. Distributed Programming: Interpreted and Compiled Web services allow processing of distributed data –Data are distributed and maintained by their custodians, –Processing nodes (web-services) are also distributed –‘Interpreted’ web-programs for data processing can be created ad hoc by end users However, ‘interpreted’ web programs are slow, fragile and uncertain –Slow due to large data transfers between nodes –Fragile due to instability of connections –Uncertain due to failures of data provider and processing nodes One solution is to ‘compile’ the data and processing services –Data compilation transforms the data for fast, effective access (e.g. OLAP) –Web service compilation combines processes for effective execution Interpreted or compiled? –Interpreted web programs are simpler and up to date but slow, fragile, uncertain –Compiled versions are more elaborate and latent but also faster and more robust –Frequently used datasets and processing chains should be compiled and kept current

7. Services Program Execution: Reverse Polish Notation Writing the WS program: - Write the program on the command line of a URL call - Services are written sequentially using RPN - Replacements Connector/Adaptor: - Reads the service name from the command line and loads its WSDL - Scans the input WSDL - The schema walker populates the service input fields from: - the data on the command line - the data output of the upstream process - the catalog for the missing data Service Execution For each service Reads the command line, one service at a time Passes the service parameters to the above Connector/Adopter, which prepares the service Executes the service It also handles the data stack for RPN

8. Application Examples

9. Next Process Why? How? When? Where? CATT: A Community Tool! Part of an Analysis Value Chain Aerosol Data Collection IMP. EPA Aerosol Sensors Integration VIEWS Integrated AerData AEROSOL Weather Data Assimilate NWS Gridded Meteor. Trajectory ARL Traject. Data TRANSPORT TrajData Cube Aggreg. Traject. AerData Cube CATT Aggreg. Aerosol CATT-In CAPITA There! Not There! Further Analysis GIS Grid Processing Emission Comparison

10. F ast A erosol S ensing T ools for N atural E vent T racking FASTNET Analysts Console Community Website