Joining Knowledge Representation and Management in Digital ... · Joining Knowledge Representation...

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Joining Knowledge Representation and Knowledge Management in Digital Libraries Katrin Weller, Isabella Peters, Wolfgang G. Stock Dept. of Information Science Institute for Language and Information HeinrichHeineUniversity Düsseldorf, Germany International Conference on Digital Libraries, Delhi, India, February 2010

Transcript of Joining Knowledge Representation and Management in Digital ... · Joining Knowledge Representation...

Page 1: Joining Knowledge Representation and Management in Digital ... · Joining Knowledge Representation and Knowledge Management in Digital Libraries Katrin Weller, Isabella Peters, Wolfgang

Joining Knowledge Representation  and Knowledge Management 

in Digital Libraries

Katrin

Weller, Isabella Peters, Wolfgang G. Stock

Dept. of Information ScienceInstitute for Language and Information

Heinrich‐Heine‐University Düsseldorf, Germany

International Conference on Digital Libraries, Delhi, India, February 2010

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Objectives & Outline

Theoretical approach: Combining…– knowledge management systems (KMS) – with knowledge representation (KR)– in digital libraries (DL). 

5

main

research questions:

focusing on…– implicit and explicit knowledge– documents‘

space

– knowledge organisation

systems (KOS) types– employees

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KM, DL and KR?

Knowledge Management (KM)

Knowledge Representation (KR)

administration of internal  and external information 

e.g. knowledge sharing 

and  information dissemination

social methods + technical  systems (KMS)

• implicit + explicit knowledge

Digital Libraries (DL)

?

?

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KM, DL and KR?

Knowledge Management (KM)

Knowledge Representation (KR)

administration of internal  and external information 

e.g. knowledge sharing 

and  information dissemination

social methods + technical  systems (KMS)

• implicit + explicit knowledge

Corporate DL!•

corporate memory + 

retrieval system•

“repositories of information 

wherein contents can be  searched or browsed”

(Pejtersen

et al., 2008) 

Digital Libraries (DL)

?

?

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KM, DL and KR?

Knowledge Management (KM)

Knowledge Representation (KR)

administration of internal  and external information 

e.g. knowledge sharing 

and  information dissemination

social methods + technical  systems (KMS)

• implicit + explicit knowledge

Corporate DL!•

corporate memory + 

retrieval system•

“repositories of information 

wherein contents can be  searched or browsed”

(Pejtersen

et al., 2008) 

Digital Libraries (DL)

?

• content descriptive metadata •

supporting access to documents: searching and 

browsing based on knowledge organization systems  (KOS)  folksonomies, classification systems, thesauri etc.

?

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Explicit & Implicit Knowledge (Question 1 & 2)

1.

Which knowledge representation methods are appropriate  to map explicit

knowledge?

(externalized) documents  +  KOS

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2.

Which knowledge representation methods are appropriate  to map implicit

knowledge?

people (as documents)  +  folksonomies

Explicit & Implicit Knowledge (Question 1 & 2)

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Documents‘

Space (Question 3)

3.

Are all documents equal in regard to knowledge  management? If not, how can we model the documents' 

space of a company?

Based on: Krause (2006)

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KOS Types (Question 4)

4.

What kinds of KOS (which can be applied in digital libraries)  do exist? Are there differences in the semantic richness of 

the types of KOS?

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Emergent Semantics (Question 5)

5.

Can we construct a corporate KOS by using the  employees' tags? 

Tag co‐occurences

as basis 

for detecting hidden 

semantic relations.

http:www.bibsonomy.org Power Tags I

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Emergent Semantics (Question 5)

Co‐occurences: 

Approach for detecting hidden semantic relations in texts.

Tags co‐occurring  with  “Web 2.0”: 

Power Tags II

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Emergent Semantics (Question 5)

Co‐occurences: 

Approach for detecting hidden semantic relations in texts.

Tags co‐occurring  with  “Web 2.0”: 

Power Tags II

Intellectual identification of semantic relations

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Conclusion

DL for KM

KR

Emergent

Semantics

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Conclusion

• Digital Libraries can be used as Knowledge Management  Systems. KOS support precise access to documents within DL.

• For handling implicit knowledge, we have to go beyond  technical solutions and focus on the people: as documents 

and as actors in social (tagging) applications. 

• Document types within the DL have to be treated differently:  the Shell Model

classifies different documents based on 

importance. 

• Different document types may be  indexed with different KOS types.

• Improvement of lightweight KOS is  possible with methods of emergent  semantics

and semantic upgrades.

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We are looking forward to your comments & questions

Isabella Peters: isabella.peters@uni‐duesseldorf.deWolfgang G. Stock: stock@phil‐fak.uni‐duesseldorf.deKatrin

Weller: weller@uni‐duesseldorf.de

Greetings from Düsseldorf!

This presentation is available on SlideShare: http://www.slideshare.net/katrinweller

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References

• Krause, J. 2006. Shell Model, Semantic Web and Web Information Retrieval.  In Information und Sprache, pp. 95‐106, edited by Harms, I., Luckhardt, 

H.D., and Giessen, H.W. Munich, Germany: Saur.

• Pejtersen, A.M., Hansen, P., and Albrechtsen, H. 2008. A Work‐Centred  Approach to Evaluation of a Digital Library: Annotation System for 

Knowledge Sharing in Collaborative Work. World Digital Libraries

1(1): 1‐17.

• Peters, I., and Weller, K. 2008a. Paradigmatic and Syntagmatic Relations in  Knowledge Organization Systems. Information –

Wissenschaft und Praxis

59(1): 100‐107.

• Peters, I., and Weller, K. 2008b. Tag Gardening for Folksonomy Enrichment  and Maintenance. Webology

5(3).

• Polanyi, M. 1967. The Tacit Dimension.

Garden City, NY: Doubleday (Anchor  Books).

This is a selection references. Please see the conference proceedings for a complete list.