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FundamentalsofInformationSystems,
SeventhEdition
Chapter 7
Knowledge Management
and Specialized
Information Systems
FundamentalsofInformationSystems,
SeventhEdition
1
PrinciplesandLearningObjectives
• Knowledgemanagementallowsorganizations
toshareknowledgeandexperienceamong
managersandemployees
– Discussthedifferencesamongdata,information,
andknowledge
– Describetheroleofthechiefknowledgeofficer
(CKO)
– Listsomeofthetoolsandtechniquesusedin
knowledgemanagement
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PrinciplesandLearningObjectives
(continued)
Artificialintelligencesystemsformabroadanddiversesetof
systemsthatcanreplicatehumandecisionmakingforcertain
typesofwell-definedproblems
– Definethetermartificialintelligenceandstatethe
objectiveofdevelopingartificialintelligencesystems
– Listthecharacteristicsofintelligentbehaviorandcompare
theperformanceofnaturalandartificialintelligence
systemsforeachofthesecharacteristics
– Identifythemajorcomponentsoftheartificialintelligence
fieldandprovideoneexampleofeachtypeofsystem
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PrinciplesandLearningObjectives
(continued)
• Expertsystemscanenableanovicetoperform
atthelevelofanexpertbutmustbe
developedandmaintainedverycarefully
– Listthecharacteristicsandbasiccomponentsof
expertsystems
– Outlineandbrieflyexplainthestepsfor
developinganexpertsystem
– Identifythebenefitsassociatedwiththeuseof
expertsystems
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PrinciplesandLearningObjectives
(continued)
• Multimediaandvirtualrealitysystemscan
reshapetheinterfacebetweenpeopleand
informationtechnologybyofferingnewways
tocommunicateinformation,visualize
processes,andexpressideascreatively
– Discusstheuseofmultimediainabusinesssetting
– Definethetermvirtualrealityandprovidethree
examplesofvirtualrealityapplications
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PrinciplesandLearningObjectives
(continued)
• Specializedsystemscanhelporganizations
andindividualsachievetheirgoals
– Discussexamplesofspecializedsystemsfor
organizationalandindividualuse
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WhyLearnAboutKnowledge
ManagementandSpecialized
InformationSystems?
• Knowledgemanagementandspecialized
informationsystemsareusedinalmostevery
industry
• Learningaboutthesesystems:
– Willhelpyoudiscovernewwaystouse
informationsystemsinyourday-to-daywork
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KnowledgeManagementSystems
• Dataconsistsofrawfacts
• Information:
– Collectionoffactsorganizedsothattheyhave
additionalvaluebeyondthevalueofthefacts
themselves
• Knowledge:
– Awarenessandunderstandingofasetof
informationandthewaysthatinformationcanbe
madeusefultosupportaspecifictaskorreacha
decision
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KnowledgeManagementSystems
(continued)
• Knowledgemanagementsystem(KMS):
– Organizedcollectionofpeople,procedures,
software,databases,anddevices
– Usedtocreate,store,share,andusethe
organization’sknowledgeandexperience
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KnowledgeManagementSystems
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OverviewofKnowledge
ManagementSystems
• Explicitknowledge:
– Objective
– Canbemeasuredanddocumentedinreports,
papers,andrules
• Tacitknowledge:
– Hardtomeasureanddocument
– Typicallynotobjectiveorformalized
• Manyorganizationsattempttoconverttacit
knowledgetoexplicitknowledge
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DataandKnowledgeManagement
WorkersandCommunitiesof
Practice
• Dataworkers:
– Secretaries,administrativeassistants,
bookkeepers,dataentrypeople,etc.
• Knowledgeworkers:
– Create,use,anddisseminateknowledge
– Professionalsinscience,engineering,orbusiness;
writers;researchers;educators;corporate
designers;etc.
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DataandKnowledgeManagement
WorkersandCommunitiesof
Practice(continued)
• Chiefknowledgeofficer(CKO):
– Top-levelexecutivewhohelpstheorganization
useaKMStocreate,store,anduseknowledgeto
achieveorganizationalgoals
• Communitiesofpractice(COP):
– Groupofpeoplededicatedtoacommondiscipline
orpractice
– Maybeusedtocreate,store,andshare
knowledge
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Obtaining,Storing,Sharing,and
UsingKnowledge
• Knowledgeworkers:
– Oftenworkinteams
– Canusecollaborativeworksoftwareandgroup
supportsystemstoshareknowledge
• Knowledgerepository:
– Includesdocuments,reports,files,anddatabases
• Knowledgemappointstheknowledgeworker
totheneededknowledge
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Obtaining,Storing,Sharing,and
UsingKnowledge(continued)
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TechnologytoSupportKnowledge
Management
• EffectiveKMS:
– Isbasedonlearningnewknowledgeandchanging
proceduresandapproachesasaresult
• Dataminingandbusinessintelligencecanhelp
captureanduseknowledge
• IBMLotusNotesandMicrosoftDashboard,
WebStoreTechnology,andAccessWorkflow
Designerareknowledgemanagementtools
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TechnologytoSupportKnowledge
Management(continued)
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AnOverviewofArtificial
Intelligence
• Artificialintelligence(AI):
– Computerswiththeabilitytomimicorduplicate
thefunctionsofthehumanbrain
• ComputersystemsthatusethenotionofAI:
– PlayJeopardy
– Helptomakemedicaldiagnoses
– Pickandtradestocks
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ArtificialIntelligenceinPerspective
• Artificialintelligencesystems:
– Includethepeople,procedures,hardware,
software,data,andknowledgeneededtodevelop
computersystemsandmachinesthat
demonstratecharacteristicsofintelligence
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TheNatureofIntelligence
• TuringTest:
– Determineswhetherresponsesfromacomputerwith
intelligentbehaviorareindistinguishablefromthosefrom
ahumanbeing
• Characteristicsofintelligentbehaviorincludetheabilityto:
– Learnfromexperiencesandapplyknowledgeacquired
fromexperience
– Handlecomplexsituations
– Solveproblemswhenimportantinformationismissing
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TheNatureofIntelligence
(continued)
• Characteristicsofintelligentbehaviorinclude
theabilityto(continued):
– Determinewhatisimportant
– Reactquicklyandcorrectlytoanewsituation
– Understandvisualimages
– Processandmanipulatesymbols
– Becreativeandimaginative
– Useheuristics
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TheBrainComputerInterface
• BrainComputerInterface(BCI):
– Ideaistodirectlyconnectthehumanbraintoa
computerandhavehumanthoughtcontrol
computeractivities
• Ifsuccessful:
– TheBCIexperimentwillallowpeopletocontrol
computersandartificialarmsandlegsthrough
thoughtalone
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TheMajorBranchesofArtificial
Intelligence
• AIisabroadfieldthatincludes:
– Expertsystemsandrobotics
– Visionsystemsandnaturallanguageprocessing
– Learningsystemsandneuralnetworks
• Expertsystems:
– Hardwareandsoftwarethatstoresknowledgeand
makesinferences,similartoahumanexpert
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TheMajorBranchesofArtificial
Intelligence(continued)
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Robotics
• Developingmechanicaldevicesthatcan:
– Paintcars,makeprecisionwelds,andperform
othertasksthatrequireahighdegreeofprecision
• Manufacturersuserobotstoassembleand
paintproducts
• Contemporaryrobotics:
– Combinebothhigh-precisionmachinecapabilities
andsophisticatedcontrollingsoftware
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VisionSystems
• Hardwareandsoftwarethatpermit
computerstocapture,store,andmanipulate
visualimagesandpictures
• Effectiveatidentifyingpeoplebasedonfacial
features
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NaturalLanguageProcessingand
VoiceRecognition
• Processingthatallowsthecomputerto
understandandreacttostatementsand
commandsmadeina“natural”language,such
asEnglish
• Voicerecognition:
– Convertingsoundwavesintowords
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LearningSystems
• Combinationofsoftwareandhardwarethat:
– Allowsthecomputertochangehowitfunctions
orreactstosituationsbasedonfeedbackit
receives
• Learningsystemssoftware:
– Requiresfeedbackonresultsofactionsor
decisions
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NeuralNetworks
• Computersystemthatsimulatesfunctioning
ofahumanbrain
• Canprocessmanypiecesofdataatthesame
timeandlearntorecognizepatterns
• Neuralnetworkprogram:
– Helpsengineerssloworspeeddrillingoperations
tohelpincreasedrillingaccuracyandreducecosts
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OtherArtificialIntelligence
Applications
• Geneticalgorithm:
– Approachtosolvingcomplexproblemsinwhicha
numberofrelatedoperationsormodelschange
andevolveuntilthebestoneemerges
• Intelligentagent:
– Programsandaknowledgebaseusedtoperform
aspecifictaskforaperson,aprocess,oranother
program
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AnOverviewofExpertSystems
• Computerizedexpertsystems:
– Useheuristics,orrulesofthumb,toarriveat
conclusionsormakesuggestions
• TheU.S.Army:
– UsestheKnowledgeandInformationFusion
Exchange(KnIFE)expertsystemtohelpsoldiersin
thefieldmakebettermilitarydecisions
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WhentoUseExpertSystems
• Peopleandorganizationsshoulddevelopan
expertsystemifitcan:
– Provideahighpotentialpayofforsignificantly
reducedownsiderisk
– Captureandpreserveirreplaceablehuman
expertise
– Solveaproblemthatisnoteasilysolvedusing
traditionalprogrammingtechniques
– Developasystemmoreconsistentthanhuman
experts
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WhentoUseExpertSystems
(continued)
• Peopleandorganizationsshoulddevelopan
expertsystemifitcan(continued):
– Provideexpertiseneededatanumberoflocations
atthesametimeorinahostileenvironmentthat
isdangeroustohumanhealth
– Provideexpertisethatisexpensiveorrare
– Developasolutionfasterthanhumanexpertscan
– Provideexpertiseneededfortrainingand
development
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ComponentsofExpertSystems
• Expertsystem:
– Consistsofacollectionofintegratedandrelated
components
• Knowledgebase:
– Storesallrelevantinformation,data,rules,cases,
andrelationshipsusedbyexpertsystem
– Createsknowledgebaseby:
• Usingrules
• Usingcases
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ComponentsofExpertSystems
(continued)
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TheInferenceEngine
• Purpose:
– Toseekinformationandrelationshipsfromthe
knowledgebase
– Toprovideanswers,predictions,andsuggestions,
likeahumanexpert
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TheExplanationFacility
• Allowsauserordecisionmakertounderstand
howtheexpertsystemarrivedatcertain
conclusionsorresults
• Example:
– Adoctorcanfindoutthelogicorrationaleofa
diagnosismadebyamedicalexpertsystem
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TheKnowledgeAcquisitionFacility
• Providesconvenientandefficientmeansof
capturingandstoringallcomponentsof
knowledgebase
• Knowledgeacquisitionsoftware:
– Canpresentusersanddecisionmakerswitheasyto-usemenus
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TheKnowledgeAcquisitionFacility
(continued)
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TheUserInterface
• Permitsdecisionmakerstodevelopanduse
theirownexpertsystems
• Mainpurpose:
– Tomakedevelopmentanduseofanexpert
systemeasierforusersanddecisionmakers
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ParticipantsinDevelopingand
UsingExpertSystems
• Domainexpert:
– Personorgroupwiththeexpertiseorknowledge
theexpertsystemistryingtocapture
• Knowledgeengineer:
– Personwhohastrainingorexperienceinthe
design,development,implementation,and
maintenanceofanexpertsystem
• Knowledgeuser:
– Personorgroupwhousesandbenefitsfromthe
expertsystem
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ParticipantsinDevelopingand
UsingExpertSystems(continued)
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ExpertSystemsDevelopmentTools
andTechniques
• Theoretically,expertsystemscanbe
developedfromanyprogramminglanguage
• Expertsystemshellsandproducts:
– Collectionsofsoftwarepackagesandtoolsusedto
design,develop,implement,andmaintainexpert
systems
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ExpertSystemsDevelopmentTools
andTechniques(continued)
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MultimediaandVirtualReality
• Useofmultimediaandvirtualreality:
– Hashelpedmanycompaniesachievea
competitiveadvantageandincreaseprofits
• Theapproachandtechnologyusedin
multimedia:
– Isoftenthefoundationofvirtualrealitysystems
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OverviewofMultimedia
• Multimediais:
– Textandgraphics
– Audio
– Videoandanimation
– Fileconversionandcompression
• Designingamultimediaapplication:
– Requirescarefulthoughtandasystematic
approach
– Requiresthattheenduseofthedocumentorfile
becarefullyconsidered
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OverviewofVirtualReality
• Virtualrealitysystem:
– Enablesoneormoreuserstomoveandreactina
computer-simulatedenvironment
• Immersivevirtualreality:
– Userbecomesfullyimmersedinanartificial,3D
worldthatiscompletelygeneratedbyacomputer
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InterfaceDevices
• Toseeinavirtualworld:
– Oftentheuserwearsahead-mounteddisplay
(HMD)withscreensdirectedateacheye
• Hapticinterface:
– Relayssenseoftouchandothersensationsina
virtualworld
– Mostchallengingtocreate
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FormsofVirtualReality
• Immersivevirtualreality
• Applicationsthatarenotfullyimmersive:
– Mouse-controllednavigationthrougha3D
environmentonagraphicsmonitor
– Stereoprojectionsystems
– Stereoviewingfromthemonitorviastereoglasses
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VirtualRealityApplications
• Medicine:
– VRprogramcalledSnowWorldhelpstreatburn
patients
• Educationandtraining:
– Virtualtechnologyhasalsobeenappliedbythe
military
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VirtualRealityApplications
(continued)
• BusinessandCommerce:
– Boeingusedvirtualrealitytohelpitdesignand
manufactureairplanepartsandnewplanes
• Entertainment:
– MoviesuseCGItobringrealismtothesilver
screen
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SpecializedSystems
• Segway:
– Usessophisticatedsoftware,sensors,andgyro
motorstotransportpeople
• RadioFrequencyIdentification(RFID)tags:
– Containsmallchipswithinformationabout
productsorpackages
– Canbequicklyscannedtoperforminventory
control
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SpecializedSystems(continued)
• Gametheory:
– Involvestheuseofinformationsystemsto
developcompetitivestrategiesforpeople,
organizations,orevencountries
• Informatics:
– Combinestraditionaldisciplines,suchasscience
andmedicine,withcomputersystemsand
technology
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Summary
• Knowledge:
– Awarenessandunderstandingofasetof
information
• Knowledgeworkers:
– Peoplewhocreate,use,anddisseminate
knowledge
• Artificialintelligence:
– Broadfieldthatincludes:
• Expertsystems,robotics,visionsystems
• Naturallanguageprocessing,learningsystems,and
neuralnetworks
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Summary(continued)
• Expertsystemconsistsofacollectionof
integratedandrelatedcomponents
• Inferenceengine:
– Processestherules,data,andrelationshipsstored
intheknowledgebase
• Virtualrealitysystem:
– Enablesoneormoreuserstomoveandreactina
computer-simulatedenvironment
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Summary(continued)
• Virtualreality:
– Canrefertoapplicationsthatarenotfully
immersive
• Specializedsystems:
– Segway
– RadioFrequencyIdentification(RFID)tags
– Gametheory
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