gio wiederhold simql 1 integration of simulation results into information systems gio wiederhold...

Gio Wiederhold SimQL 1

Integration of Simulation Results into Information Systems

Gio Wiederhold

April 2002, updated Nov 2002


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) Often 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 *******


Decision-making (DM)

Analyze Alternatives

• Current Capabilities

• Future Expectations

Process tasks:

• List resources

• Enumerate alternatives

• Prune alternative

• Compare alternatives

futurenow


Prediction Requires Tools

E-mail this book, Alfred Knopf, 1997


Future information systems

Combine data from the past, with current data, knowledge, and predictions into the future

o oo o

o o

Assessment of the values of alternative possible outcomes


DM support is disjoint

Distribution

Databases

Simulation

Planning Science

extensions to moveto networked supportare also disjoint

does not interoperate


Current state of DM Support

• Spreadsheets

• Planning of allocations

• Other simulations

various point assessments

past now futurepast now futuretimetime

Data integration

distributed, heterogeneous

x17 @qbfera ffga 67 .78 jjkl,a nsnd nn 23.5a

Databases

Intuition +

organized support disjointed support


Information Systems should alsoProject 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

timetimepast now futurepast now future


New Resources for Information

Application Layer

Mediation Layer

Foundation Layer

data and simulation resources

value-added services

decision-makers at workstations


Interfaces enable integration:SimQL to access Simulations

timetimepast now futurepast now future

Msgsystems,sensors

Databases, accessed via SQL or

XML, CORBA compliant wrappers

Simulations, accessed via SimQL and

compliant wrappers


Parser

MetadataManager

Querymanager

SchemaManager

Wrapped .. SimulationsMetadata

DevelopmentInteraction

Production Interaction

Filing ofAccessSpecs

Use of AccessSpecs

Initiation and Results of Simulations

SchemaCommands

SchemaCommands

Help

Errorreports

CustomerDeveloper

Help

Query

Prototype ImplementationPrototype Implementation


Stanford experiment, supported by DARPA & NIST

Phase 1 Architectures

SpreadsheetsEngineering

wrapper wrapperwrapper

LogisticsApplication

ManufacturingApplication

Weather (short-, long-term)

wrapper

TestData

SimQL accessSimQL access

SimQL access

SQL access


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 < name of wrapper accessing web pages >

WHERE Date = `tomorrow' AND Location = `ORD'.

-----> { (75, .8), (.30,.8), (5, .8), (NW, .8) }

Would prefer XML representation


5 DevelopAssessment Plan

7

2 Develop *Objectives

*: w/Measures

4 AssignTask / Activity

3 Phase & *SequenceObjectives

1Determine

StatusExecution 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’mtsDetermine

Assess and/orRehearse Plan

SimQL

Place of SimQL in Objective-based Planning

from JFACC PIP

Simulationresults

Simulationparameters


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.


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 developmentDBMS technology developmentreuse of infrastructure

Today• most new systems use a

DBMS for data storageeven 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 developmentsimulation technology develop’treuse of infrastructure

Objective• build information systems

combining DBMS, Simulationseven with less performance, inability to handle all problems,but enough of them . . .


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


Use of Simulation Results

Simulation results can be composed for alternative Courses-of-actionsComposition should include computation

and recomputation of likelihoods Likelihoods change as now moves forwards

and eliminates earlier alternatives.

timetime0.40.4

0.60.6

0.20.2

0.50.5

0.30.3

0.50.5

0.20.20.10.1

0.10.1

0.10.1

0.030.030.070.07

0.10.1

0.50.5 0.30.3

0.20.2

prob


The branches can be labeled with probabilities, then assessed using the outcome with values

past now futurepast now future

Next period alternatives

0.4

0.6

& subsequent periods

0.2

0.1

0.5

0.30.2

0.1

0.1

0.13

0.3

0.2

0.07

0.4

0.3

0.1

10001000

20002000

50005000

10001000

00

-6000-6000

-3000-3000

ValuesValues

100100

600600

1100 5001100 500

200 200200 200

-420 0-420 0

-820 -400-820 -400

12001200

6666

134134

-1220-1220

12661266

--10861086

timetime

prob

value


Integrating data & planning support will make our data reusable and much more valuable

past now futurepast now future

Re-assess as timeRe-assess as timemarches forward !marches forward !

A Pruned Bush A Pruned Bush

Databases, . . .Spreadsheets,

other simulations,

Msgssensors

10001000

20002000

50005000

10001000

00

100 100

600600

1100 5001100 500

200 200200 200

00

12001200

6666

timetime

1266 ?1266 ?

?? ??


Even the present needs SimQL

timetimepastpast now now futurefuture

last recorded observations

simple simulationsto 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:


Recent State of SimQL Research

Spreadsheets Weather Civil Engineering

wrapper wrapper wrapper

Test Application

GUIcollect language

requirements


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?


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


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?


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


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.


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


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


• 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 ?

gio wiederhold simql 1 integration of simulation results into information systems gio wiederhold...

Documents