(Apologies for cross-postings of this announcement.)

 

CALL FOR PAPERS

===============

 

SPECIAL ISSUE IN KNOWLEDGE-BASED SYSTEMS ON

 

ENHANCING EXPERIENCE REUSE AND LESSON LEARNING

 

 

CONTEXT

=======

Knowledge-based systems (KBS) intend to provide end-users with knowledge

access and reasoning in specific subject domains. One of the main objectives

of KBS is to share expert knowledge and to enhance knowledge reuse and

learning. From a technical point of view, such systems generally incorporate,

at least, a knowledge base, an inference engine, and a user interface.

 

However, the elaboration of knowledge models issued from expert interviews

and/or from document repositories is known to be a difficult and expensive

task. For the last few years, alternative approaches for knowledge-based

systems elaboration have been explored to overcome this difficulty. They

focus on the representation and reuse of experiences, which can be defined

as knowledge in action, knowledge used during the achievement of a particular

task. These approaches favor contextualized, shared and reusable, lessons-

learned oriented knowledge engineering.

 

Contextualization: experiences closely relate to actual activities.

Contextual information (a context consists of a set of facts and a

description of an environment within which those facts are believed to be

true) can easily be modeled and linked to relevant knowledge that may be

either used or produced by activities.

 

Sharing: an important issue of experience-based systems is to facilitate

the sharing of experiences over time (from one project to another for

instance) and over space (from an organization to another for instance).

Since actors contribute to activities with their viewpoints and with

specialized skills and knowledge it is important to share experiences

and to promote collaborative reuse.

 

Reuse: the reuse of experiences is a key inference mechanism for practical

experience-based systems. These mechanisms should enable to find appropriate

experiences that have been already capitalized and to integrate them in

current activities and roles.

 

Lessons-learning: fragments of knowledge collected over time and space should

be analyzed to produce more general knowledge such as best practices and

lessons-learned.

 

From a practical point of view, effective experience reuse and lessons-learned

are increasingly important assets of enterprises and represent sources of

competitive advantages in various domains such as systems design and engineering,

quality management, maintenance, dependability engineering, risk management,

diagnosis, planning and project management, etc.

 

From a technical point of view, different underlying models and techniques

have been elaborated and used to improve knowledge contextualization and

facilitate its reuse such as case-based and trace-based reasoning, experience

feedback and lessons-learned systems.

 

AIMS AND SCOPE

==============

This special issue aims at:

- focusing on the formalisms and tools that are relevant to model experiences

  and facilitate their reuse,

- providing an overview on theoretical and empirical research related to

  experience-based systems and lessons-learned systems,

- gathering research works from multiple disciplines (information system,

  artificial intelligence, industrial engineering, medical services or else…)

  with applications and to compare worldwide approaches and practices.

 

However, this special issue will not focus on research on processing of

statistical data (monitored process data), data mining, or data warehousing

since these approaches are not directly based on the formalization of

experience produced by human activity.

 

RELEVANT TOPICS

===============

Examples of interesting topics are (but are not limited to):

- Formalization of experiences (or traces, episodes, evidences…);

- Formalization of case studies;

- Reuse and generalization of experiences;

- Reasoning with experience, particularly case-based reasoning,

  trace-based systems, agent-based approaches, ontologies, conceptual

  graphs, rough sets, Belief theory…

- E-learning approaches based on learning experiences

- Interoperability and integration of different lessons learned systems

  and experience management systems

- Integration of lessons learned and experience management systems in

  information systems such as PLM, CAD, CSCW systems.

 

IMPORTANT DATES

===============

Submission deadline: 30 January 2013

First notification: 15 May 2013

Re-submission: 15 September 2013

Second notification and final acceptance: 15 December 2013

Camera-ready: January 2014

 

RECOMMENDATIONS TO THE AUTHORS

==============================

- Contributions are invited in the form of original high-quality research

  and review papers (preferably no more than 20 double line spaced manuscript

  pages, including tables and figures), following the formatting style for

  Elsevier.

- A submission that has already been published in conference proceedings has

  to be submitted as more than 35% update in comparison to the published

  version.

- The title page should not include name, affiliation, and e-mail address of

  the authors.

- All paper have to be submitted through the journal electronic submission

  EES, http://ees.elsevier.com/knosys/.

 

Full recommendations are available in KBS or Elsevier websites:

http://www.journals.elsevier.com/knowledge-based-systems/

http://www.elsevier.com/wps/find/journaldescription.cws_home/525448/authorinstructions

 

GUEST EDITORS

=============

Prof. Eric Bonjour, Université de Lorraine, France, eric.bonjour@univ-lorraine.fr

Prof. Laurent Geneste, ENIT, France, laurent.geneste@enit.fr

Prof. Ralph Bergmann, University of Trier, Germany, bergmann@uni-trier.de

 

_______________________________________________________________________

Prof. Dr. Ralph Bergmann                      Office: + 49 651 201 3876

University of Trier                            Sekr.: + 49 651 201 3875

Department of Business Information Systems II    Fax: + 49 651 201 3396

54286 Trier, Germany

E-Mail: bergmann@uni-trier.de

Web:    www.wi2.uni-trier.de

_______________________________________________________________________