CFP: EKAW 2010

International Conference on Knowledge Engineering and Knowledge  
Management
EKAW 2010

Lisbon, Portugal,
http://ekaw2010.inesc-id.pt

The 17th International Conference on Knowledge Engineering and  
Knowledge Management is concerned with all aspects of eliciting,  
acquiring, modeling and managing knowledge, and its role in the  
construction of knowledge-intensive systems and services for the  
semantic web, knowledge management, e-business, natural language  
processing, intelligent information integration, etc.

The focus of the 17th edition of EKAW will be on "Knowledge Management  
and Engineering by the Masses".

The call for papers in PDF available at
http://ekaw2010.inesc-id.pt/docs/cfpEkaw2010.pdf

Important dates

* Submission: 19th of March 2010
* Notification: 14th of May 2010
* Camera Ready: 11th of June 2010

Organizing Committee

* General and PC chairs:
   - Sofia Pinto (INESC-ID, Lisbon)
   - Philipp Cimiano (CITEC, Universität Bielefeld)

* Workshop chair:
   - Siegfried Handschuh (DERI, NUI Galway)

* Tutorial chair:
   - Victoria Uren (University of Sheffield)

Demonstration chairs:
   - Oscar Corcho (UPM, Madrid)
   - Johanna Völker (University of Mannheim)

The proceedings of the conference will be published by Springer Verlag  
in the LNCS series. The LNCS volume will contain contributed papers.
EKAW 2010 will also feature a tutorial and workshop program, as well  
as a poster and demo track. Poster/demo notes and workshop/tutorial  
notes will be published separately in a companion booklet.

Paper submission and reviewing for EKAW 2010 will be electronic via  
the EasyChair conference submissions site. Submissions should be 15  
pages long (max) formatted according to Springer Verlag LNCS guidelines.

EKAW 2010 welcomes papers dealing with theoretical, methodological,  
experimental, and application aspects. In particular, but not  
exclusively, we solicit papers about methodologies, models, and tools  
for the following topics:

1) Knowledge Management

* Methodologies and tools for knowledge management
* Aspects of collaboration, distribution and evolution of knowledge in  
KM
* Advanced knowledge modeling languages and tools
* Best practices / experiences in KM
* Foundations of KM
* Entity-oriented approaches to KM
* Layered intelligence in knowledge management
* Provenance, reliability and trust in knowledge management
* Knowledge management for collaboration and decision support
* Methods for accelerating take-up of KM technologies
* Corporate memories for KM
* Case-based reasoning for KM

2) Knowledge Engineering and Acquisition

* Methodologies for knowledge engineering
* Knowledge acquisition, ontology learning
* Knowledge sharing
* Knowledge evolution
* Collaborative knowledge engineering
* Design patterns
* Techniques for knowledge acquisition based on machine learning, NLP  
etc.
* Uncertainty and vagueness in knowledge modeling
* Knowledge engineering and software engineering
* Ontology localization
* Ontology alignment
* Evolution of knowledge (including ontology evolution)
* Knowledge acquisition from non-ontological resources (thesauri,  
folksonomies, lexica etc.)
* Knowledge acquisition and knowledge integration from heterogeneous  
sources (multimedia and 3D data, databases, sensor data streams,  
social interaction data)
* Knowledge authoring and knowledge markup languages
* Ontology evaluation
* Dynamic, distributed and process knowledge (including web services,  
grid services, P2P systems, rules and business processes, problem  
solving methods, procedural knowledge)
* Agent-based approaches to knowledge management
* Knowledge mashups

3) Knowledge In Use:
knowledge management and engineering for

* Retrieval and proactive delivery of pertinent knowledge
* Multimedia applications
* Life and E-sciences
* E-Government and public administration
* Health and medicine
* Automotive and manufacturing industry
* Semantic desktop applications
* The legal domain
* Cultural heritage applications
* Digital broadcasting and film, game and 3D media content production  
and sharing
* Digital libraries
* Virtual worlds
* Storytelling
* Management in critical applications
* Organizing user-contributed content
* Transition across organizations

4) Social and Cognitive Aspects of Knowledge Engineering

* Sustainability and cost analysis of knowledge engineering
* Human-knowledge interaction
* Cognitive systems and knowledge engineering
* Knowledge ecosystems
* Knowledge and social network analysis & modeling
* Knowledge in trust networks
* Personal sphere in knowledge engineering and management
* Collaborative and social approaches to knowledge management and  
acquisition

5) Special focus knowledge management and engineering by the masses

* Human-machine synergy in knowledge acquisition
* Incentives for knowledge creation and semantic annotation
* Enhancing human productivity (e.g. knowledge workers)
* Social and human factors in knowledge management
* Collective and collaborative intelligence in knowledge management
* Social tagging and folksonomies, social networks
* Web2.0 approaches to KM (including semantic wikis, folksonomies, etc.)
* Games with a Purpose and KM
* Linked Open Data / Web of Data

As an important difference to earlier conferences, EKAW will accept  
different types of papers. The papers will all have the same status  
and follow the same formatting guidelines in the proceedings but will  
receive special treatment during the reviewing phase. In particular,  
each paper type will be subject to own evaluation criteria. The PC  
will also make sure that there is a reasonable balance of the paper  
types accepted. At submission time the paper has to be clearly  
identified as belonging to one of the following categories.

A) Standard research papers

These are "standard" papers presenting a novel method, technique or  
analysis with appropriate empirical or other types of evaluation as  
proof-of concept. The main evaluation criteria here will be  
originality, technical soundness and validation.

B) In-use papers

Here we are expecting papers describing applications of knowledge  
management and engineering in real environments. Applications need to  
address a sufficiently interesting and challenging problem on real and  
large datasets, involving many users etc. The focus is less on the  
originality of the approach and more on presenting real, large-scale  
and complex systems that solve a significant problem. Technical  
details to understand how the problem is solved are required.  
Evaluations should involve real users of a system rather than  
representing a pure academic exercise.
The papers will be evaluated according to the significance and  
practical relevance of the described research as well as with respect  
to the technical soundness of the described solution and accompanying  
evaluation.

C) Problem Analysis papers

We invite researchers to also publish problem analysis papers which do  
not present any novel method, technique or approach to solving a  
problem, but help to understand the problem itself. Understanding the  
characteristics of a problem itself is an important task in research  
and can benefit many people working on the same or at least similar  
problems. We expect in-depth discussions and analysis of a certain  
phenomenon or problem, with
clear definitions as well as qualitative and quantitative analyzes of  
the main characteristics of the problem. We also expect a reasonable  
review of the state-of-the-art stating in how far current solutions  
fall short. Papers will mainly be evaluated with respect to how  
general and technically sound their problem analysis is and how useful  
it will be for other researchers working on the same problem. We  
expect that such papers will guide future research by highlighting  
critical assumptions, motivating the difficulty of a subproblem or  
explaining why current techniques are not sufficient, all corroborated  
by quantitative and qualitative arguments. Evaluation criteria will  
also include appropriate categorization of the problem area and  
description of present solutions and approaches; and appropriate  
description of the limitations of the present solutions and approaches.

D) Validation papers

A fundamental characteristic of research is that it should be  
reproducible. In some disciplines, reproduction of results by others  
is a basic research activity. We would like to encourage researchers  
to reproduce and validate methods, results and experiments etc.  
proposed by others before in a new context or application, on new  
datasets, under new assumptions etc. The goal is clearly to reach  
interesting and significant new conclusions about the method/approach  
in question that warrant a stand-alone publication. The reproduction  
of results should thus lead to new knowledge about the method in  
question or reveal inherent problems in the assumptions of the  
original research or limitations of previous solutions. Papers will be  
evaluated with respect to the soundness of the rationale for  
reproducing a certain approach as well as with respect to the new  
knowledge that is generated by reproducing the approach in question. A  
clear comparison between the results obtained through the reproduction  
and the original results are mandatory.



Prof. Dr. Philipp Cimiano
Semantic Computing Group
Cognitive Interaction Technology
Center of Excellence (CITEC)
Bielefeld University
33615 Bielefeld
Germany

Mail.: cimiano@cit-ec.uni-bielefeld.de
Phone: +49 (0) 521 106 12249
Web.: http://www.cimiano.de

Room: Q2-110 (see http://www.uni-bielefeld.de/Universitaet/Ueberblick/Anreise/campus.html 
)

Received on Saturday, 31 October 2009 14:55:28 UTC