IIS WS 2010/11 IIS WS 2010/11
Prof. Dr. Rainer Manthey Prof. Dr. Rainer Manthey
Wednesday
Wednesday, 9 , 9 –– 11 a.m.11 a.m.
A 207 A 207
Intelligent Information Systems
- WS 2010/11 -
Intelligent Information Systems Intelligent Information Systems
- - WS 2010/11 - WS 2010/11 -
(MA-(MA-INF 3203)INF 3203)
Vita Rainer Manthey Vita Rainer Manthey
1953 Wilhelmshaven 1953
19531953 WilhelmshavenWilhelmshavenWilhelmshaven
1973 Kiel 1973 Kiel 1973 Kiel 1973 Kiel
1984 München 1992 Bonn
1992 Bonn 1992 Bonn 1992 Bonn
University of Kiel University of Kiel
Informatics/Mathematics Informatics/Mathematics
S
Studenttudent (Diploma 1979)(Diploma 1979) ResearchResearch assistant (PhD 1984)assistant (PhD 1984)
European Computer
European Computer--Industry Industry Research Centre (ECRC) Research Centre (ECRC) ResearcherResearcher// TeamleaderTeamleader University of Bonn
University of Bonn P
Professorrofessor
1984 M
1984 Müünchennchen
Intelligent Databases Group Intelligent Databases Group
Prof. Dr. Rainer Manthey Dr. Andreas Behrend
Dipl.-Inform. Yvonne Christ
• Since 1.6.1992
• At present:
2 Research assistants 2 PhD students
9 thesis candidates
• Completed since 1994:
4 Dissertations 1 Master thesis 185 Diploma theses
Databases Programming
Languages
Artificial Intelligence
Main research areas:
• Deductive and active databases
• Declarative programming
• Automated reasoning
• Data stream monitoring
IDB Group at Bonn University IDB Group at Bonn University
IIS in Bonn
IIS in Bonn‘‘s Master Curriculum (1)s Master Curriculum (1)
Algorithmics Algorithmics
Graphics, Graphics, Vision, Vision, Audio Audio
Information &
Information &
Communication Communication
Management Management
Intelligent Intelligent Systems Systems Classification of this lecture within Bonn‘s MSc curriculum
Classification
Classification of of thisthislecturelecture withinwithinBonn‘Bonn‘s s MScMSc curriculumcurriculum
IIS in Bonn
IIS in Bonn‘‘s Master Curriculum (2)s Master Curriculum (2)
Communication Communication
Management Management Information
Information Management Management
IIS in Bonn
IIS in Bonn‘‘s Master Curriculum (3)s Master Curriculum (3)
Information Information
Systems Systems
Software Software Engineering Engineering Intelligent IS
Intelligent IS
IM SubIM Sub--curriculumcurriculum
At presentAt present, , thethe followingfollowing modulesmodules areare „on „on offeroffer““ in thein the areaarea of Information Management:of Information Management:
•• in WS:in WS:
•• 3203: Intelligent Information Systems 3203: Intelligent Information Systems
(Lecture(Lecture; 6 ; 6 creditscredits; ; Prof. MantheyProf. Manthey))
•• 3301: 3301: SpatialSpatialInformation Systems Information Systems
(Lecture(Lecture; 6 ; 6 creditscredits; ; PD Dr. SteinhagePD Dr. Steinhage))
•• in SS:in SS:
•• 3302: Temporal Information Systems 3302: Temporal Information Systems
(Lecture(Lecture; 6 ; 6 creditscredits; ; Prof. MantheyProf. Manthey))
•• everyeverysemestersemester ((normallynormally):):
•• 3210: 3210: SelectedSelected Topics in Intelligent Information SystemsTopics in Intelligent Information Systems (Seminar; 4
(Seminar; 4 creditscredits; ; Prof. MantheyProf. Manthey))
•• 3213: 3213: AdvancedAdvanced Topics in Information Management Topics in Information Management
(Lecture(Lecture; 6 ; 6 creditscredits; different ; different lecturerslecturers, , thisthis semestersemester; Jun.; Jun.--ProfProf. Markowetz. Markowetz))
•• 3214: 3214: SelectedSelected Topics in Information ManagementTopics in Information Management (Seminar; 4
(Seminar; 4 creditscredits; different ; different lecturerslecturers))
•• 3305: Information Systems 3305: Information Systems (Lab; 9
(Lab; 9 creditscredits; different ; different lecturerslecturers thisthis semester; semester; Jun.Jun.-Prof-Prof. . MarkowetzMarkowetz))
IntelligentIS
IntelligentIS: Module Description: Module Description
120120 66
11stst
Schedule WS 2010/11 Schedule WS 2010/11
2626 2424
1919 1717
1212 1010
January January
2222 2020
1515 1313
88 66
1 1 29
29 December
December
2525 2222
17 17 15
15
1010 88
33 11
November November
2727 2525
22 3131
February February
2020 1818
1313 1111
October October
WedWed MonMon
13 exercises13 exercises 13 lectures13 lectures
relevant relevant forfor
final
final examexam All Saints Day
All Saints Day
Dies academicus Dies academicus
Exercises
Exercises and Examsand Exams: : „„RulesRules of of thethe Game“Game“
•• Exercises:Exercises:
•• In In thethe samesame roomroomeveryeveryMondayMonday 99--11 11 a.ma.m..––forfor entireentire auditoriumauditorium, no , no smallsmall groupsgroups. .
•• ExercisesExercisesheldheldbyby Prof. Manthey himselfProf. Manthey himself
•• Goals: Goals:
•• To makeTo make youyoufit forfit for thethe exam!exam!
•• To provideTo provide somesome„hands„hands on“on“ experienceexperience withwith
•• ParticipationParticipationwill notwill not bebe checked, checked, butbut isis stronglystrongly recommended!!recommended!!
•• For gettingFor getting admissionadmission to examsto exams: :
•• TwoTwowrittenwritten teststestswill bewill be organizedorganized duringduring exercisesexercises (dates(dates to beto be announced).announced).
•• Minimal requirementsMinimal requirements forfor passingpassingthesetheseteststeststo beto be announced, announced, tootoo..
•• FailureFailure in testsin tests meansmeans no admissionno admission to examsto exams!!
•• Registration: Registration: NowNow ––enterenter youryour detailsdetailsintointo list circulatedlist circulated (Latecomers(Latecomers: Send : Send mailmail!)!)
•• Exams:Exams:
•• WrittenWritten examsexams forfor bothboth examexamdatesdates (MSc(MSc: 6 : 6 creditscredits, DPO 2003: 4 , DPO 2003: 4 creditscredits))
•• ExamExamdatesdates to beto be negotiated: negotiated: Most
Most likelylikely end of February/earlyend of February/early MarchMarch + end of March+ end of March
•• DPO 1998: May beDPO 1998: May be partpart of a B orof a B or C examC exam (combined(combined withwith otherother lectures)lectures)
•• Registration: to Registration: to bebe announcedannounced
Intelligent IIS Homepage Intelligent IIS Homepage
http://www.iai.uni-bonn.de/III//lehre/vorlesungen/IntelligentIS/WS10/
http://www.iai.uni
http://www.iai.uni--bonn.de/III//lehre/vorlesungen/IntelligentIS/WS10/bonn.de/III//lehre/vorlesungen/IntelligentIS/WS10/
Slides
Slides forforDownloadDownload
PDF copies of all slides will be provided after
each lecture for download!
PDF copiesPDF copies of all slidesof all slides will
will bebe providedprovided afterafter
eacheachlecturelecture forfor download!download!
No textbook for this lecture – but additional reading material via the homepage!
No textbookNo textbook forfor thisthislecturelecture–– butbutadditional readingadditional reading materialmaterial via thevia the homepage!homepage!
Intelligent IS:
Intelligent IS: WhatWhat DoesDoes itit MeanMean? (1) ? (1)
„Intelligent information system“
is a rather recently coined notion, not yet well-defined or established!
„Intelligent „Intelligent informationinformation system“system“ isisa rathera rather recentlyrecently coinedcoined notion,notion, notnotyetyet well-well-defineddefined oror established!established!
Intelligent IS:
Intelligent IS: WhatWhat DoesDoes itit MeanMean? (2)? (2)
12.10.2010 12.10.2010 12.10.2010
„Intelligent database“
better represented – claimed to be coined in 1989!
„Intelligent „Intelligent databasedatabase““ better
better representedrepresented ––claimedclaimedto beto be coined
coined in 1989!in 1989!
Intelligent IS:
Intelligent IS: WhatWhat DoesDoes itit MeanMean? (3)? (3)
Probably
Probably thethefirstfirst bookbook on theon the issueissue byby Parsaye, Parsaye, Chignell
Chignell, , KhoshafianKhoshafian, , and Wongand Wong,,
published
published byby John Wiley John Wiley in 1989
in 1989 –– still availablestill available,, butbut a a bitbit outdatedoutdated! !
Intelligent IS:
Intelligent IS: WhatWhat DoesDoes itit MeanMean? (4)? (4)
„Intelligent information system“
is a notion used by many in
science as well as industry by now!
„Intelligent „Intelligent informationinformation system“system“ isis a notiona notion usedusedbyby manymany inin
science
science as well as industryas well as industry byby now!now!
Intelligent IS:
Intelligent IS: WhatWhat DoesDoes itit MeanMean??(5)(5)
Google Scholar:
Quite a number of scientific publi- cations, but not too many (yet)!
Google Scholar:Scholar: Quite
Quite a a numbernumber of of scientificscientificpublipubli-- cations
cations, , butbut notnottootoo manymany (yet(yet)!)!
Expl. 1: Journal of Intelligent IS Expl. 1: Journal of Intelligent IS
Intelligent information systems:
„integrating artifical intelligence and database techniques“
Intelligent
Intelligent informationinformation systems:systems:
„integrating„integrating artificalartificalintelligenceintelligence and databaseand database techniques“techniques“
Expl. 2: Intelligent IS Research Lab at Penn State Expl. 2: Intelligent IS Research Lab at Penn State
Expl. 3: Intelligent IS Systems Institute at Cornell University Expl. 3: Intelligent IS Systems Institute at Cornell University
Expl. 4: IIS Group at Hildesheim University Expl. 4: IIS Group at Hildesheim University
Expl. 5: IIS Unit at Boeing Expl. 5: IIS Unit at Boeing
ManyManyNotionsNotions––Almost SimilarAlmost Similar ConceptsConcepts –– Different Different TraditionsTraditions and Stylesand Styles!!
Expert
Expert system system
Knowledge
Knowledge- -based based system system
Deductive
Deductive database database
Decision
Decision support support system system Intelligent
Intelligent information information system system
Business
Business intelligence intelligence
Agent
Agent system system
Intelligent IS
Intelligent IS „à„à la Bonn“la Bonn“: : ReasoningReasoning overoverDBsDBswithwithDBMS TechniquesDBMS Techniques
•• ThereThere arearelots of lots of interpretationsinterpretationsof of thethenotionnotion „IIS„IIS““ byby nownowout thereout there: : somesome moremore, some, some lessless focused
focused and and concreteconcrete. . HoweverHowever, , therethere isis no no agreementagreement on on thethe meaningmeaning of of thisthis notionnotion ((yetyet).).
•• In In BonnBonn, , wewe interpretinterpret„„intelligent intelligent informationinformation systemssystems““in in thethe traditiontraditionof of integratingintegrating resultsresults fromfromartificialartificial intelligenceintelligence and databasesand databases whichwhichstartedstarted aboutabout 25 years25 years agoago..
•• TheThe AIAI aspectaspect concentratesconcentrates on „on „intelligentintelligent““ reasoningreasoning overover datadatarepresentingrepresentinga fractiona fraction of of
„the„the world“world“. . ReasoningReasoning isis donedone in order toin order to
•• AnalyseAnalyse thethe datadata in order to betterin order to better understandunderstanditsits properties,properties,
•• CheckCheckthethe consistencyconsistencyand qualityand quality of theof the datadata bybycontrollingcontrolling itsits modifications,modifications,
•• ReactReact to eventsto events consideredconsidered relevant.relevant.
•• TheThe DBDB aspectaspect concentratesconcentrates on conceptson concepts forfor representingrepresentingand methodsand methods forfor efficientlyefficiently exploiting
exploiting nonnon-factual-factual knowledge:knowledge:
•• ViewsViews––as as specificationsspecificationsof of derivationderivation rulesrules
•• ConstraintsConstraints––as as specificationsspecifications of consistencyof consistency--preservingpreserving rulesrules
•• TriggersTriggers––as as specificationsspecificationsof intelligent reactionsof intelligent reactions to DB eventsto DB events..
This is our approach to the ideal of a truely „intelligent IS“ – there are certainly others!
ThisThis isisourour approachapproach to theto the ideal of a ideal of a truelytruely„intelligent IS„intelligent IS““–– therethereareare certainlycertainly others!others!
At theAt the corecore of IIS: Theoryof IIS: Theory and and PracticePractice of Deductiveof Deductive DatabasesDatabases
ThisThis approachapproach––whichwhichisis a speciala special oneone–– explains
explains thethedrawingdrawing on theon the title slidetitle slide ofof thisthis lecture.lecture.
Therefore Therefore::
Theory
Theory and Practiceand Practice of theof the establishedestablished research
research areaareaof of „Deductive„Deductive Databases“Databases“ will
will bebe at theat the corecoreof thisof this lecturelecture..
In additionIn addition, , wewe will motivatewill motivate conceptsconcepts byby meansmeansof of practicalpracticalexamplesexamples fromfrom thethe modern modern areaarea of of streamstream monitoringmonitoring. .
OurOurCurrentCurrent ApplicationApplicationScenarioScenario forfor IIS Technology: Intelligent MonitoringIIS Technology: Intelligent Monitoring SystemsSystems
DBMSDBMS
Analysis software Analysis software
Application Application-- specific
specific methods methods
Stream
Stream of of sensorsensor datadata
Monitoring
Monitoring Systems: ApplicationSystems: ApplicationSpectrumSpectrum
• Traffic:
• transport networks, airtraffic control
• streets/motorways (traffic jams, toll)
• logistics („fleet management“)
• military („battlefield surveillance")
• Environment:
• extreme events in nature (catastrophes, weather phenomena)
• animal behaviour (bird migration)
• Administration:
• case surveillance (courts, tax authorities, exams offices)
• Finance:
• banks: account transactions, credibility of debitors
• stock market: stock rates, portfolio management
• Trade:
• automatic store and order management
• Healthcare:
• patient monitoring (intensive care, Homecare/Telecare)
• epidemiology (cancer, epidemic diseases)
• Sports: playing field surveillance (wireless tracking)
•• Traffic:Traffic:
•• transporttransportnetworks, networks, airtrafficairtraffic controlcontrol
•• streets/motorwaysstreets/motorways (traffic(traffic jams, toll)jams, toll)
•• logisticslogistics(„(„fleetfleet management“management“) )
•• militarymilitary („(„battlefieldbattlefield surveillance")surveillance")
•• Environment:Environment:
•• extreme eventsextreme events in nature (catastrophesin nature (catastrophes, , weatherweather phenomenaphenomena))
•• animalanimalbehaviourbehaviour(bird(bird migrationmigration))
•• AdministrationAdministration::
•• casecasesurveillancesurveillance (courts(courts, tax , tax authoritiesauthorities, , examsexams offices)offices)
•• FinanceFinance: :
•• banks: banks: accountaccount transactions, transactions, credibilitycredibility of of debitorsdebitors
•• stock marketstock market: stock : stock ratesrates, , portfolioportfolio managementmanagement
•• Trade:Trade:
•• automaticautomatic storestore and order managementand order management
•• Healthcare:Healthcare:
•• patientpatientmonitoringmonitoring(intensive care(intensive care, , Homecare/TelecareHomecare/Telecare))
•• epidemiologyepidemiology (cancer(cancer, , epidemicepidemic diseasesdiseases))
•• Sports: Sports: playingplaying fieldfieldsurveillancesurveillance ((wirelesswireless tracking)tracking)
„Vision„Vision““: DB Systems : DB Systems PerformingPerforming Analysis of Analysis of StreamStream DataData
DBMSDBMS
Analytical data Analytical
Analytical data data
Analysis
Analysis methodsmethods
Views
Views and Query Processingand Query Processing as a Key to as a Key to Knoweldge-Knoweldge-BasedBased StreamStreamAnalysisAnalysis
DBMSDBMS
Secondary
Secondary datadata
Virtual
Virtual analytical analytical data data
Primary
Primary datadata
++++ ++++
(event(event log, streamlog, stream datadata)) (domain(domain knowledgeknowledge in factin fact format)format)
Continuous
Continuous queries/views queries/views
(Domain
(Domain knowledgeknowledgeinin rulerule format)format)
• ViewsViews and pre-defined continuouscontinuous queries: queries
Declarative specifications of specificspecific domain knowledge
• Query Query processingprocessing in the DBMS: GenericGeneric inference methods for new data
Optimizing ETL jobs Optimizing ETL jobs
In cooperation with
Stochastic Analysis of Stochastic Analysis of Radar Data
Radar Data
In cooperation with
Analyzing Stock Market Data Analyzing Stock Market Data Air Traffic Control
Air Traffic Control
In cooperation with and Current
Current Projects on Intelligent Analysis of Data StreamsProjects on Intelligent Analysis of Data Streams in Bonnin Bonn
Expected
Expected BackgroundBackground
•• ThisThis lecturelectureisis intendedintended to beto be an advancedan advanced lecturelecture in thein the areaarea of informationof information systems.systems.
•• Thus, Thus, beginnersbeginnersin thisin this branchbranch of computerof computer sciencescience will mostwill most certainlycertainly bebe in thein the wrongwrong place.place.
•• I expectI expect everybodyeverybody to haveto have a solida solid (if(if notnotgood) backgroundgood) background in fundamentalsin fundamentals of informationof information management
management, in , in particularparticular in relational databasesin relational databases includingincluding SQLSQLand relational and relational algebraalgebra..
•• So, ifSo, if youyou havehavedifficultiesdifficultiesin understandingin understanding somethingsomethinglikelike this, this, youyou will havewill have a harda hard timetime ifif youyoucontinuecontinue attending:attending:
•• But: But: ThereThereisis a chancea chance eveneven forfor thosethose notnot „fit„fit““in SQL, as in SQL, as wewe areare goinggoingto useto use a newa new andand different relational
different relational languagelanguage mostmost of of thethetime: time: DatalogDatalog
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