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Designing Knowledge Infrastructures Organizations and Society in Information Systems (OASIS) 2004 Workshop December, 12th, 2004. Ronald Maier Dept. of Management Information Systems, Information Systems Leadership Martin-Luther-University Halle-Wittenberg. Overview. Motivation - PowerPoint PPT Presentation
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Designing Knowledge Designing Knowledge InfrastructuresInfrastructures
Organizations and Society in Information Organizations and Society in Information Systems (OASIS) 2004 WorkshopSystems (OASIS) 2004 Workshop
December, 12th, 2004December, 12th, 2004
Ronald MaierRonald Maier Dept. of Management Information Systems, Dept. of Management Information Systems,
Information Systems LeadershipInformation Systems Leadership
Martin-Luther-University Halle-WittenbergMartin-Luther-University Halle-Wittenberg
M anagem ent In form ation
System s
Inform ation System s
Leadership
Knowle
dge
Man
age
men
t
Leadersh ip
Business processes
Info
rmat
ion
Sys
tem
s
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
OverviewOverview
• MotivationMotivation
• Enterprise Knowledge Infrastructures (EKI)Enterprise Knowledge Infrastructures (EKI)
• Framework for integrated design of knowledge workFramework for integrated design of knowledge work
• DiscussionDiscussion
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
• Multiple terms used vaguelyMultiple terms used vaguely
– knowledge (management) infrastructure, knowledge warehouseknowledge (management) infrastructure, knowledge warehouse
– organizational memory systemorganizational memory system
– KM tools, software, combination of tools applied with KM in mindKM tools, software, combination of tools applied with KM in mind
– KM platforms, suites, systemsKM platforms, suites, systems
• What separates knowledge infrastructures from more traditional IS?What separates knowledge infrastructures from more traditional IS?
– Intranet infrastructures,Intranet infrastructures,
– document and content management systems,document and content management systems,
– artificial intelligence tools,artificial intelligence tools,
– business intelligence tools,business intelligence tools,
– Groupware or collaboration tools,Groupware or collaboration tools,
– e-learning systems,e-learning systems,
• What can we learn from this for modeling knowledge work?What can we learn from this for modeling knowledge work?
Knowledge InfrastructuresKnowledge Infrastructures
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
specifics ofknowledge
advancedknowledge services
KMinstruments
comprehensiveplatform
acquistion processes deployment processes
goals
capture,organize
store,package
search,retrieval
transfer,(re-)use
revision,feedback
participants,communities
Definition of Knowledge InfrastructureDefinition of Knowledge Infrastructure
• a comprehensive ICT platform • for collaboration and knowledge
sharing• with advanced knowledge
services built on top that are– contextualized,– integrated on the basis of a
shared ontology and– personalized– for participants networked in
communities.
• foster the implementation of KM instruments
• in support of knowledge processes
• targeted at increasing organizational effectiveness.
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
Knowledge work…Knowledge work…
• solves solves weakly structured problemsweakly structured problems with a high degree of with a high degree of varietyvariety and and exceptionsexceptions,,
• is is creative workcreative work and requires creation, acquisition, application and distribution of and requires creation, acquisition, application and distribution of knowledgeknowledge,,
• uses uses intellectual abilitiesintellectual abilities and and specialized knowledgespecialized knowledge rather than physical rather than physical abilities,abilities,
• requires a high level of requires a high level of educationeducation, , trainingtraining and and experiencesexperiences resulting in resulting in skillsskills and and expertiseexpertise,,
• is often is often organized decentrallyorganized decentrally using new organizational metaphors, using new organizational metaphors,
• bases inputs and outputs primarily on bases inputs and outputs primarily on datadata and and informationinformation,,
• has strong has strong communicationcommunication needs and is highly needs and is highly mobilemobile and and distributeddistributed,,
• and thus requires a strong yet flexible support by and thus requires a strong yet flexible support by information and information and communication technologiescommunication technologies..
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
Architecture of Knowledge InfrastructureArchitecture of Knowledge Infrastructure
Intranet/Extranet:messages, contents
of CMS,E-lear-ning platforms
data fromRDBMS,
TPS, data warehouses
content fromInternet,
WWW,newsgroups
DMS documents,files from office
informationsystems
data fromexternal online
data bases
VI – data and knowledge sources
personalinformation
manage-ment data
V – infrastructure servicesIntranet infrastructure services (e.g., storage, access, messaging,
security services); extract, transformation, loading, inspection services …
IV – integration servicessemantic integration based on ontologies; user, function, process
integration
III – knowledge services
publicationstructuring,contextualization
discoverysearch, visuali-zation, navigation
collaborationcompetence mgmt.,community spaces
learningauthoring, coursemgmt., tutoring
II – personalization servicesidentity management; person-, process-, project- or role-oriented
knowledge portals
knowledge worker
I – access servicesauthentication; transformation for diverse applications and
appliances
specifics ofknowledge
advancedknowledge services
KMinstruments
comprehensiveplatform
acquistion processes deployment processes
goals
capture,organize
store,package
search,retrieval
transfer,(re-)use
revision,feedback
participants,communities
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
KM InstrumentKM Instrument
Definition Definition ICT-supported KM instrument:ICT-supported KM instrument:
• consist of an aligned collection of organizational, HRM and ICT measuresconsist of an aligned collection of organizational, HRM and ICT measures
• that can be deployed purposefully in order to achieve knowledge-related goals,that can be deployed purposefully in order to achieve knowledge-related goals,
• independent of a particular knowledge domain.independent of a particular knowledge domain.
person(knowledge bound
to individuals)
product(knowledgeas object)
organization(knowledge in social systems)
competencemanagement
communities/knowledgenetworks
lessons learned
good/bestpractices
semantic contentmanagement
knowledgedevelopment/application
maps
knowledge
process
reengineering
personalexperience
management
knowledgestructuremapknowledge
source map
specifics ofknowledge
advancedknowledge services
KMinstruments
comprehensiveplatform
acquistion processes deployment processes
goals
capture,organize
store,package
search,retrieval
transfer,(re-)use
revision,feedback
participants,communities
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
Knowledge ProcessesKnowledge Processes
lessonslearned
good/bestpractices
redesignedbusinessprocesses
personalexperience
management
level of commitment & legitimation
Ind ividua lknowled ge
K nowledgeinuse
A pp lica tio n
Sha ring In ter- sub jectiveknowled ge
Institu tio na liza tio n
Institutiona lizedknowled ge
Feed -ba ck
Acq
u isi
tion
Ind ivid ua llea rning
Rep a ckag ing
Rep ro du ctio n
Selling
Interna lco m m unica tio n
K nowledge sources
K nowledgeproducts &services
3O rg an iza tio n a l learning cycle
O rg.Lea rning
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
Designing EKI – Modeling for Knowledge WorkDesigning EKI – Modeling for Knowledge Work
targ
et g
roup
,
netw
ork/
com
mun
ity type of
knowledge
KM instrument
KPR
subj
ect
cont
ext
theme
context
KM strategy,competencies
motive,outcome
occa
sion,
mod
e
person product
process
communication
organizationalstructure
skill/ interest structuretaxonomyontology
meta-datascope
goal,input,output
role
responsib
ility kno“flow” ofwledge
resource
expert
event,condition,action
productivity infrastructure
function/interaction
architecture/structure
profileoccu
rrence
content/
structu
re
personalization
naviga
tion
stru
ctur
eto
olsu
ppor
t
Ronald Maier
Martin-Luther-University Halle-Wittenberg
Lehrstuhl für W irtschaftsinform atik,insbesondere betrieb-
liches Inform ations-m anagem ent
Wis
sens
ma
na
gem
ent
IS -Führung
G eschä ftsprozesseIn
form
atio
nssy
stem
e
ResearchResearch QuestionsQuestions
• How do we model knowledge work?How do we model knowledge work?
– knowledge as product vs. process vs. knowledgeable peopleknowledge as product vs. process vs. knowledgeable people
– completeness vs. understandabilitycompleteness vs. understandability
– concepts for analysis versus design of knowledge workconcepts for analysis versus design of knowledge work
– person, product, process, productivity toolsperson, product, process, productivity tools
• How do we support it with knowledge infrastructures?How do we support it with knowledge infrastructures?
– task, knowledge, community, learning spacestask, knowledge, community, learning spaces
– seamless integration of personal and organizational KM environmentseamless integration of personal and organizational KM environment
– inter-organizational knowledge infrastructures - standardizationinter-organizational knowledge infrastructures - standardization
• How do we measure success?How do we measure success?
– productivity of knowledge workproductivity of knowledge work
– success of knowledge infrastructuressuccess of knowledge infrastructures
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