1. COMMUNITY

2. Data Acquisition and Usage Value Chain

3. Data Processing Value Chain Monitor Store Data 1 Monitor Store Data 2 Monitor Store Data n Monitor Store Data m IntData1 IntDatan IntData2 Virtual Int. Data

4. Information Processing Value Chain (Taylor, 1975) Informing Knowledge ActionProductive Knowledge InformationData Organizing Grouping Classifying Formatting Displaying Analyzing Separating Evaluating Interpreting Synthesizing Judging Options Quality Advantages Disadvantages Deciding Matching goals, Compromising Bargaining Deciding Forces to Move Data one-shot to reusable form External force – contracts Internal – humanitarian, benefits Resistances to Move Data Mechanical Personal Institutional

5. Assigning maintenance responsibility (Wiederhold) a. Source data quality – supplier database, files, or web pages b. Interface to the source– wrapper, supplier or vendor for supplier c. Source selection – expert specialist in mediator d. Source quality assess. – customer input to mediator e. Semantic interoperation – specialist group input to the mediator f. Consistency & metadata – mediator service operation or warehouse g. Informal, integration – client services with customer input h. User presentation– client services with customer input Services Sources Customers

6. Standard Data Support System Data management systems, DBMS Data processing end exploration tools Presentation tools

7. PM/Haze Data Flow in Support of AQ Management There are numerous organizations in need of data relevant to PM/Haze Most interested parties (stakeholders) are both producers and consumers of PM and haze data There is a general willingness to share data but there are many physical and organizational resistances to data flow and processing RPO Regional Planning Orgs FLM Federal Land Managers EPA EPA Regul. & Research Industry Academic NARSTO Other: Private, Academic SuperSite Shared PM/Haze Data PM and haze data are used for may parts of AQ management, mostly in form of Reports The variety of pertinent (ambient, emission) data come from many different sources To produce relevant reports, the data need to be ‘processed’ (integrated, filtered aggregated)

8. PM/Haze Data Flow in Support of AQ Management PM and haze data are used for may parts of AQ management, mostly in form of Reports The variety of pertinent (ambient, emission) data come from many different sources To produce relevant reports, the data need to be ‘processed’ (integrated, filtered aggregated) Data from multiple measurements are shared by their providers or custodians Data are integrated, filtered, aggregated and fused in the process of analysis Reports use processed data for Status and Trends; Exposure Assessment; Compliance

9. Data Re-Use and Synergy Data producers maintain their own workspace and resources (data, reports, comments). Part of the resources are shared by creating a common virtual resources. Web-based integration of the resources can be across several dimensions: Spatial scale:Local – global data sharing Data content:Combination of data generated internally and externally The main benefits of sharing are data re-use, data complementing and synergy. The goal of the system is to have the benefits of sharing outweigh the costs. Content User Local Global Virtual Shared Resources Data, Knowledge Tools, Methods User Shared part of resources

10. Integration for Global-Local Activities Global Activity Local Benefit Global data, toolsImproved local productivity Global data analysisSpatial context; initial analysis Analysis guidance Standardized analysis, reporting Local Activity Global Benefit Local data, tools Improved global productivity Local data analysisElucidate, expand initial analysis Identify relevant issuesResponsive, relevant global analysis Global and local activities are both needed – e.g. ‘think global, act local’ ‘Global’ and ‘Local’ here refers to relative, not absolute spatial scale

11. Content Integration for Multiple Uses (Reports) Data from multiple measurements are shared by their providers or custodians Data are integrated, filtered, aggregated and fused in the process of analysis Reports use processed data for Status and Trends; Exposure Assessment; Compliance The creation of the needed reports requires data sharing and integration from multiple sources.

12. DATAFED Rationale As much as possible, data should reside in their respective home environment. ‘Uprooted’ data in centralized databases need updated and maintained. Data Providers would need to ‘open up’ their SQL data servers for limited data subsets and queries, in accordance with a ‘contract’. However, the data structures of the Providers will not need to be changed. Retrieval of uniform data from the data warehouse facilitates integration and comparison along the key dimensions (space, time, parameter, method) The open architecture of DATAFED and the use of web-standards promotes the building tools by and for the community: Data Viewers, Data Transformers and Integrators, Report Generators, Renderers etc..