The document outlines a manifesto for a standard on meaningful representations of knowledge in social knowledge management (KM) environments, emphasizing the need for new ways to represent knowledge activities and interactions within their context. It highlights the limitations of current standards and the necessity for a shift towards an activity-oriented view that captures dynamic processes and contextual information. Recommendations include forming collaborations for standardization and focusing on specifications that consider technological advances in KM.

1. Manifesto for a Standard on Meaningful
Representations of Knowledge in Social
Knowledge Management Environments
Bick, M., Hetmank, L., Kruse, P., Maier, R., Pawlowski, J.M.,
Peinl, R., Schoop, E., Seeber, I., Thalmann, S
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3. Current Team
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4. Knowledge Management – changing
landscapes and instruments
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5. Knowledge Management Focus Areas
Intellectual Enterprise
Asset Focus Effectiveness Focus
Maximize building and Maximize use of knowledge
IV. value value reallocation of
intellectual capital
assets; operational
effectiveness
III. process
knowledge balance sheet, knowledge-intensive
scorecard, skill data bases business processes,
citation & impact analysis knowledge processes,
workflow patterns
IV. collaborative
Maximize effectiveness of Use IT to maximize capture,
people-centric learning transformation, storage,
organization retrieval and development of
knowledge
competencies, motiva-
I. human tion, roles & responsi-
bilities, task patterns
semantics, knowledge
workplace and infrastructure,
II. IT
services, tools
People IM & IT
Focus Focus
After Wiig 1999, 158
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6. Source: B.D. Solis: http://www.sortingthoughts.de/blog/wp-
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content/uploads/2008/12/2735401175_fcdcd0da03.jpg
Knowledge Management going social…

7. The challenges
 Knowledge management trends
 Connecting human and technology orientation
 From document/repository orientation to
distributed resources and activities
 Social software as a central concept for
connecting resources and activities
 How do we represent knowledge and connect
activities, resources and people?
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8. The role of social software in knowledge
activities
 Knowledge cannot completely be codified and shared
 Knowledge transfer can be improved by capturing information
about the current and historical context and the underlying
activity.
 Social media (SM) and social software (SSW) support knowledge
transfer and construction of knowledge through social
interactions between people.
 Contextual information of interactions can be tracked by using
existing SM and SSW functionalities such as activity streams,
tagging and commenting
 SM and SSW are mostly limited to personal and content metadata
 Standardization remains a key task for improving the handling of
large and complex information
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9. Current standardization efforts
 Technical standards (document formats,
metadata)
 Dublin Core
 Learning Object Metadata (LOM)
 Business Process Model Notation (BPMN)
 IMS Learning Design Specification
 Contextualized attention metadata (CAM)
 RDF, OWL
 OOXML, PDF, ODF
 Human-oriented standards (guidelines and good
practices)
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10. Knowledge activities
To deal with the (automatic ) detection of the users’ task and activities based on collected contextual data a
better understanding of potential knowledge activities and their connection and traceability is necessary.
Author Knowledge (Management) Activity Author Knowledge (Management) Activity
Aurum et al., knowledge creation, knowledge Alavi 2001 Creation, storage/retrieve, transfer, apply,
2008 acquisition, knowledge identification,
knowledge adaptation, knowledge
organization
knowledge distribution, knowledge
application
Newell et al., create knowledge, integrate Fong and Acquisition, creation, storage, distribution, use,
2009 knowledge, share knowledge Choi, 2009 maintaining
codify knowledge
Hädrich, 2008 Identification, acquisition Holsapple, acquisition (identifying appropriate knowledge,
Codification, combination Singh, capturing identified knowledge, organizing
Distribution, search & retrieval 2001 captured knowledge, transferring the organized
application, development knowledge
archiving & deleting, learning selection (identifying appropriate knowledge,
networking capturing identified knowledge, organizing
Nonaka & Socialization, externalization, captured knowledge, transferring organized
Takeuchi, combination, internalization knowledge)
1995; Nonaka generate (monitor, evaluate, produce, transfer)
& Toyama, assimilation (assessing, targeting, structuring,
2003 delivering)
emission (targeting, producing, transferring)
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11. Activity Stream
Activity Streams allow applications to publish a live stream of a persons’
working, learning (or social) activities by aggregators that serialize items into
a sequence of posts, making actions visible to other users of the service.
Motivation
 participants better understand boundaries
of their actions
 groups better manage & coordinate activities
 people decide with whom to collaborate
 attracts attention and signals
 enhances knowledge sharing, asking &
answering questions, solving problems
 enhances mechanisms to demonstrate
competences
(Olson et al., 2006)
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12. Active Documents
 An electronic document which includes data as well as metadata and
application logic. Alternatively, an active document can be directly
connected with the application logic.
 Metadata and application logic will be transferred with the active
document and be able to activate, control and execute functionalities.
[Trög07]
Integration of Ability to react Ability to initiate and Ability to take
Transformation metadata on an event control functions decisions autonomously
characteristic
Passive Enriched Reactive Active Proactive
Document Document Document Document Document
Sort of document
<creator>Muster</creator> <creator>Muster</creator> <creator>Muster</creator> <creator>Muster</creator>
<date>11-01-2006</date> <date>11-01-2006</date> <date>11-01-2006</date> <date>11-01-2006</date>
Requirements
regarding system Specific system
Specific system environment interpreting
environment Standard system enviroment environment
metadata and application logic
using autoactivation mode
[Trög07]
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13. Current findings
 Knowledge management changes towards
distributed, social, interactive environments
 Current standards do not allow appropriate
representation of social KM
 E.g. activities
 New ways of knowledge representations are
needed (and approaches are available)
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14. The Manifesto
 New ways of knowledge representation
 Key aspects
 Represent activities and interactions
 Represent context: in which environment do
knowledge activities happen?
 Allow bundling, merging and connecting resources,
activities and people
 Develop a standard for KM (systems) to enable
interoperability and re-use
 A basis for discussion, discourse, community
building!
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15. New conceptualization to support
knowledge sharing
New Concepts Description
Knowledge Activity (KA) Goal directed actions within a user's context
Knowledge Activity Stream (KAS) Time-ordered list of knowledge activities (user-centric
view)
Knowledge Trace (KT) Codified representation of a user's action that captures
contextual information
Contextual Information Information, e.g. time, place, actions performed on
knowledge objects as well as related people and their skills
Knowledge Object (KO) Codified knowledge of externalized knowledge (e.g.
paragraphs, tables, figures, mind maps)
Knowledge Bundle (KB) Collection of knowledge traces that are affiliated to a
knowledge object (object-centric perspective)
Knowledge Container (KC) A set of knowledge objects and their corresponding
knowledge bundles
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16. Towards knowledge containers
KA1 KA2
A A A A A A
KO
KAS1
KO KO
KB
KAS2
reference
KA – Knowledge Activity
A – Action
KT – Knowledge Trace KO KO
KO – Knowledge Object
KB – Knowledge Bundle
KC – Knowledge Container
A KB A KB
KAS – KA Stream
KC

17. Aspects of contextual information
enriched knowledge containers
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18. Predictions and Recommendations
1. Acknowledge KM as a social activity
• gap between technology and human orientation bridged by SSW and SM
• trend acknowledged by research community and practitioners.
2. Focus the active, not the passive
• we need a variety of ways to represent knowledge
• the focus should shift from document-oriented to an activity-oriented
view to better capture the dynamic process.
3. Context will be the key factor to understand KM
• context rarely analyzed or represented in both, research and
standardization communities, thus lack of transferability of results
• adequate specifications needed to represent context.
4. Stop using outdated frameworks
• standards in KM like Dublin Core do not take technological advances into
account
• widely agreed conceptual KM framework needed considering social
media as source for contextual metadata.
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19. Predictions and Recommendations (2)
5. Focus on specifications and standards
• KM community has ignored standards for decades.
• specifications and standards are important when designing and
experimenting with innovative systems.
6. Form an enterprise-research alliance for standards
• consensus of all stakeholders needed, in particular researchers and
enterprises.
• a balanced community needs to be formed from the very beginning.
7. Stand on the shoulders of giants
• KM community has specific characteristics, but standards do not need to
be created from scratch.
• build on existing base and similar standards already successful in use.
8. Create standards now
• KM and SSW are mature enough that we understand the key success
factors.
• KM community needs to create standards as an agreement in the
community for competitive innovative and interoperable solutions
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20. Summary
 We need new ways of representing knowledge
management in standards
 Key aspect: adding context and activities
 Steps
 Find (further) appropriate
approaches, standards and alternatives
 Collaborate with standardization bodies
 Discuss, test, improve!
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21. Contact Information JYU
Prof. Dr. Markus Bick
mbick@escpeurope.eu
Prof. Dr. Ronald Maier
ronald.maier@uibk.ac.at
Prof. Dr. Jan M. Pawlowski
jan.pawlowski@jyu.fi
Prof. Dr. Rene Peinl
rene.peinl@hof-university.de
Prof. Dr. Eric Schoop
eric.schoop@tu-dresden.de
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