2. Gio Wiederhold SimQL 1 Integration of Simulation Results into Information Systems Gio Wiederhold April 2002, updated Nov 2002

3. Gio Wiederhold SimQL 2 Information Integration Information Integration provides new Information for improved Decision Making when it  presents more data (mediation 1991)  Risk: much may be irrelevant  captures new relationships (knowledge bases 1977)  O ften requires expert inter-domain knowledge  includes current sensor data (fusion, streams 1999)  Data reflect the past only  includes predictions about future courses ******* A new, potentially major topic *******

4. Gio Wiederhold SimQL 3 Decision-making (DM) Analyze Alternatives Current Capabilities Future Expectations Process tasks: List resources Enumerate alternatives Prune alternative Compare alternatives future now

5. Gio Wiederhold SimQL 4 Prediction Requires Tools  E-mail this book, Alfred Knopf, 1997

6. Gio Wiederhold SimQL 5 Future information systems Combine data from the past, with current data, knowledge, and predictions into the future o o o o o o Assessment of the values of alternative possible outcomes

7. Gio Wiederhold SimQL 6 DM support is disjoint Distribution Databases Simulation Planning Science extensions to move to networked support are also disjoint does not interoperate

8. Gio Wiederhold SimQL 7 Current state of DM Support Spreadsheets Planning of allocations Other simulations various point assessments past now future time Data integration distributed, heterogeneous x17 @qbfera ffga 67.78 jjkl,a nsnd nn 23.5a Databases Intuition + organized support disjointed support

9. Gio Wiederhold SimQL 8 Information Systems should also Project into the Futures Support of decision-making requires dealing with the futures, as well the past Databases deal well with the past Sensors can provide current status Spreadsheets, simulations deal with the likely futures Information systems should be able to combine all three time past now future

10. Gio Wiederhold SimQL 9 New Resources for Information Application Layer Mediation Layer Foundation Layer data and simulation resources value-added services decision-makers at workstations

11. Gio Wiederhold SimQL 10 Interfaces enable integration: SimQL to access Simulations time past now future Msg systems, sensors Databases, accessed via SQL or XML, CORBA compliant wrappers Simulations, accessed via SimQL and compliant wrappers

12. Gio Wiederhold SimQL 11 Parser Metadata Manager Query manager Schema Manager Wrapped..Simulations Metadata Development Interaction Production Interaction Filing of Access Specs Use of Access Specs Initiation and Results of Simulations Schema Commands Schema Commands Help Error reports CustomerDeveloper Help Query Prototype Implementation

13. Gio Wiederhold SimQL 12 Stanford experiment, supported by DARPA & NIST Phase 1 Architectures Spreadsheets Engineering wrapper Logistics Application Manufacturing Application Weather (short-, long-term) wrapper Test Data SimQL access SQL access

14. Gio Wiederhold SimQL 13 Language - simple for demo SQL SELECT Temperature, Cloudcover, Windspeed, Winddirection FROM WeatherDB WHERE Date = `yesterday' AND Location = `ORD'. ----> {75,.30, 5, NW} SimQL PREDICT Temperature, Cloudcover, Windspeed, Winddirection FROM WeatherSimulation WHERE Date = `tomorrow' AND Location = `ORD'. -----> { (75,.8), (.30,.8), (5,.8), (NW,.8) } Would prefer XML representation

15. Gio Wiederhold SimQL 14 5 Develop Assessment Plan 7 2 Develop * Objectives *: w/Measures 4 Assign Task / Activity 3Phase & * Sequence Objectives 1 Determine Status Execution Feedback Higher Level Objectives, Intel, OB, ROE, Commanders Guidance & Intent, Etc. Plan Assessment Feedback Resource Constraints Required Resources Phased Sequenced Objectives Assessment Plan Prioritized Sequenced Tasks Campaign Status Access to Simulations Req’mts Determine Assess and/or Rehearse Plan SimQL Place of SimQL in Objective-based Planning from JFACC PIP Simulation results Simulation parameters

16. Gio Wiederhold SimQL 15 Types of simulation services 1. Continously executing : weather prediction –SimQL result reports best match samples 2. Execution specific to query : what-if assessment –may require HPC power for adequate response 3. Past simulations collect results in a base : materials –performs inter- or extra-polations to match query parameters 4. Combinations, i.e., 2. + 3.: top layer simulation using stored partial lower level results: device performance in new setting 5. Human-in-the-loop (mediated by an agent program): SAFs Note A simulation service program can be written in any language A simulation service must be compliant to the interface spec.

17. Gio Wiederhold SimQL 16 Enabling Interoperation Databases serve clients via SQL by Sharing a Model (The Schema) A query language over the model the SQL interface enables independence of application development DBMS technology development reuse of infrastructure Today most new systems use a DBMS for data storage even with less performance, inability to handle all problems, but enough of them well enough. Simulations should serve clients via SimQL by Sharing a Model (research q.) A query language over the model a SimQL interface enables independence of application development simulation technology develop’t reuse of infrastructure Objective build information systems combining DBMS, Simulations even with less performance, inability to handle all problems, but enough of them...

18. Gio Wiederhold SimQL 17 Internet requirements Ubiquitous access to simulations of a wide variety of types Rapid response to parameter changes –often High-Performance computation is needed –distributed simulations with synchronization Rapid Service Composition –High bandwidth among simulations –Access to multiple services in parallel

19. Gio Wiederhold SimQL 18 Use of Simulation Results Simulation results can be composed for alternative Courses-of-actions Composition should include computation and recomputation of likelihoods Likelihoods change as now moves forwards and eliminates earlier alternatives. time 0.4 0.6 0.2 0.5 0.3 0.50.20.1 0.1 0.1 0.03 0.07 0.1 0.5 0.3 0.2 prob

20. Gio Wiederhold SimQL 19 The branches can be labeled with probabilities, then assessed using the outcome with values past now future Next period alternatives 0.4 0.6 & subsequent periods 0.2 0.1 0.5 0.30.2 0.1 0.13 0.3 0.2 0.07 0.4 0.3 0.1 10002000500010000-6000-3000Values 100 100 600 600 1100 500 200 200 200 200 -420 0 -420 0 -820 -400 1200 66 66 134 134-1220 1266 - 1086 time prob value

21. Gio Wiederhold SimQL 20 Integrating data & planning support will make our data reusable and much more valuable past now future Re-assess as time marches forward ! A Pruned Bush  A Pruned Bush Databases,... Spreadsheets, other simulations, Msgs sensors 10002000500010000 100 600 600 1100 500 200 200 200 200 0 1200 66 66 time 1266 ? ??

22. Gio Wiederhold SimQL 21 Even the present needs SimQL time past now future last recorded observations simple simulations to extrapolate data Is the delivery truck in X? Is the right stuff on the truck? Will the crew be at X? Will the forces be ready to accept delivery? point-in-time for situational assessment Not all data are current:

23. Gio Wiederhold SimQL 22 Recent State of SimQL Research Spreadsheets Weather Civil Engineering wrapper Test Application GUI collect language requirements

24. Gio Wiederhold SimQL 23 SimQL research questions How little of the model needs to be exposed? How can defaults be set rationally? How should expected execution cost be reported? How should uncertainty be reported? Are there differences among application areas that require different language structures? Are there differences among application areas that require different language features? How will the language interface support effective partitioning and distribution?

25. Gio Wiederhold SimQL 24 Why not use DB-like storage? Volume is large -- – multiple future alternatives Value is transient –tomorrow all values must be updated –expect high write/read ratio jut the opposite of typical DB operations

26. Gio Wiederhold SimQL 25 Research questions for Decision Support How to move seamlessly from the past to the future? How can multiple futures be managed (indexed)? How can multiple futures be compared, selected? How should joint uncertainty be computed? How can the NOW point be moved automatically?

27. Gio Wiederhold SimQL 26 Interfaces enables research integration Research on Multiple futures –Uncertainty in databases Probability estimation –Expert Systems uncertainty –Fuzzy algebra –Prade algebra Planning Models –allocation and distribution –reduction to current values Risk management –beta estimation Distribution Databases Simulation Planning Science

28. Gio Wiederhold SimQL 27 Prediction as a Service Server is an independent contractor, defines service Client selects service, and specifies parameters Server’s success depends on value provided Some form of payment received for services x,y Databases are a current example. Simulations have the same potential.

29. Gio Wiederhold SimQL 28 Summary of SimQL A new service for Decision Making : follows database paradigm –( by about 25 years ) coherence in prediction –displacement of ad-hoc practices seamless information integration –single paradigm for decision makers simulation industry infrastructure –investment has a potential market –should follows database industry model: Interfaces promote new industries

30. Gio Wiederhold SimQL 29 Definitions of Integration Data Integration: presenting data from multiple sources so that a suite of applications* can deal with it a single (perhaps virtual) database Information integration: presenting information, obtained by processing data and metadata from multiple sources so that an suite of application can deal with it as a coherent information resource. * application suite:: a set of applications (collect, maintain, query, analyze) that have a consistent domain model Application integration: Interoperating processes. The ideal of open systems Standards are more difficult, because of hidden semantics

31. Gio Wiederhold SimQL 30 Application Integration I [Hergula]: include data extracted (via wrappers or transformers) by functions from multiple applications. Application Integration II: Use a workflow model to integrate processes into a higher level representation. Application Integration III: Creating new, higher-order (query,...) functions by combining existing application functions and made-to- order functions (in SQL,...) Defining Application Integration ?