Knowledge Networks: Discovering network structure and patterns using Social Network Analysis
Integrating Taxonomies and Folksonomies for Enhanced Knowledge Navigation (ITFEKN 2008)
Next Generation Corporate KM Systems
Technologies for Knowledge Management
Knowledge Management for Service Innovation

WS1 will be merged with WS5 and WS4 will be merged with WS2.

WS3 has been canceled. So when going to registration page, you should not select workshop #3.

Workshop Paper Submission

Papers must be formatted in the style of the Springer Publications format for LNCS. Use Author Guideline. The length of each paper should not exceed 12 pages. Short papers with 6 or less pages are also welcome. Send your papers to each workshop chairs. About WS2, please refer to paper submission in WS2 descriptions.

  • WS1: To:,
  • WS2: To:
  • WS3: To:
  • WS4: To:
  • WS5: To:,
New Important dates for WS1, WS4 and WS5:

  • Workshop paper submission deadline : 10 October 2008
  • Notification of paper acceptance : 19 October 2008
  • Camera-ready of accepted paper : 4 November 2008
  • Workshop day : 21 November 2008

Workshop 1:
Knowledge Networks: Discovering network structure and patterns using Social Network Analysis

Workshop description

During the last decade, knowledge has become a key consideration in our economies and it is heavily associated with innovation. Alongside this, so-called knowledge networks have arguably come to play a central role in organizations. These networks, which are built on social relations between employees, might serve various purposes such as collaborative problem solving, seeking advice, or developing competences by learning from peers. Recently, the network perspective has gained interest in the domain of knowledge networks and involves the study of the structure and patterns of knowledge networks. These studies rely heavily on theory and tools from social network analysis that has already a longstanding tradition in the sociology domain. The tools and techniques developed in this domain can be fruitfully applied in the field of knowledge networks. These techniques and tools can be used as (1) assessment tools and (2) research instruments.

As an assessment tool, social network analysis can be used to visualize and analyze for instance the advice seeking relations in an organization. Through visual inspection of the sociogram and by calculating network metrics such as average shortest path, connectedness or centralization, it is possible to detect potential bottlenecks in the advice seeking network of the organization. However, there is not much consensus yet about the network metrics that should be used. Furthermore, there is hardly any benchmark data available to determine e.g. if a certain value for the average shortest path is too high or not. Finally, in many cases it is not known what the structure of an ideal knowledge network looks like and how a particular instance of a knowledge network is deviating from that ideal state.

Secondly, social network analysis can also be used as a research instrument to study how the structure and patterns of knowledge networks are related to other variables such as task, group and organizational performance or to demographic data of people in the network. Much of the research so far has focused on a limited number of network metrics that are typically studied individually: interaction effects are neglected. Furthermore, group level performance also did not receive much attention yet.

Regardless of how social network analysis is used, in both cases it is necessary to collect social network data. This is typically done using interviews and/or surveys, which is a labor intensive task. Recently, also other ways of collecting network data have been explored such as mining e-mail traffic (only header or also content information) or the archives of online community forums. The advantage of this way of data collection is that it is less labour intensive and at the same time offers to do longitudinal analysis for studying the dynamics of knowledge networks. However, there has not been much research that studies if communication networks, i.e. e-mail traffic, actually resemble knowledge networks.

The workshop aims to bring together researchers from different disciplines that are interested in the application of social network analysis tools and techniques in knowledge network research. As such, the workshop provides a platform: 1) to elaborate on frequently used and emerging research questions and 2) to evaluate methodology used and, 3) to compare results of different research settings. We welcome both theoretical and empirical papers that employ diverse methodologies and philosophical perspectives.

Suggested topics (but not limited to this list)

  • Influence of network position/network pattern on individual/ group/organizational performance
  • Tools for harvesting mail messages and online communities for knowledge network data
  • Case studies concerning the application of SNA to study knowledge networks in organizations
  • Research that studies the factors that influence the formation of knowledge networks
  • Case studies concerning the analysis of knowledge networks based on e-mail data
  • Relation of knowledge networks to other networks such as friendship or communication networks
  • Tools that track, map, and visualize knowledge networks
  • Dynamics of networks, i.e. evolution of networks over time
  • Application of cluster algorithms to detect knowledge networks/communities of practice in social network data
  • Effects of social network technologies on the structure of knowledge networks

Workshop Chairs

  • Dr. Remko Helms, Faculty of Science, Department of Information and Computing Sciences, Utrecht University, Netherlands (
  • Dr. Miha Škerlavaj, Faculty of Economics, Department for Management and Organization, University of Ljubljana, Slovenia (

Program committee

  • Andrea Back, University of St Gallen, Switzerland
  • Elaine Ferneley, University of Salford, United Kingdom
  • Allatta Joan, Purdue University, United States
  • Emmanuel Lazega, University of Lille I, France
  • Claudia Müller, University of Stuttgart, Germany
  • Tobias Müller-Prothman, Pumacy Technologies AG, Germany
  • Jurriaan van Reijsen, Utrecht University, Netherlands
  • Chunke Su,University of Texas at Arlington, United States
  • Robin Teigland, Stockholm School of Economics, Sweden


  • Dr. Remko Helms:
  • Dr. Miha Škerlavaj:

Currently we are investigating if there is a possibility to publish the best papers in a special issue of a journal, e.g. Journal of Knowledge Management or Knowledge Management Research and Practice.

Workshop 2:
Integrating Taxonomies and Folksonomies for Enhanced Knowledge Navigation (ITFEKN 2008)

Workshop Objectives

The Integrating Taxonomies and Folksonomies for Enhanced Knowledge Navigation (ITFEKN 2008) workshop is the international workshop on advances to synergy folksonomy and taxonomy to create a hybrid with benefits for enhanced knowledge navigation. This workshop is to be held in conjunction with 7th International Conference on Practical Aspects of Knowledge Management (PAKM2008).

Taxonomy is a top-down communication model, which it is commonly used in information systems particularly for content management and knowledge management systems. However, it does not cater for the prevailing context of the captured information to support knowledge navigation, search and retrieval. In addition, knowledge seekers usually are posited with their experiences with the Internet, email, phone and mobile hand-held devices. These experiences will undoubtedly affect the knowledge seekers behavior in navigating and searching knowledge from knowledge repositories. With the emergence of Web 2.0, social tagging software on web sites has seen the mass creation of personalized tags for marking user-generated content (UGC). Such tags, called folksonomy are uncontrolled, non-hierarchical, incomplete, possibly redundant and even inconsistent. However, folksonomy are easy to encode, dynamic, abundant, and reflect the prevailing context and norms of the creators and the environment. Therefore, integrating folksonomy into taxonomy will create new navigational facets to support enhanced knowledge navigations to improve knowledge searching, retrieval and navigation in a dynamic environment.

The aim of this workshop is to encourage activities in this topic and to bring together world-wide researchers to discuss current challenges on integrating folksonomies and taxonomies to support knowledge searching, retrieval, and navigation. A formal framework or benchmark for evaluating taxonomy and folksonomy integration frameworks will also be discussed at this workshop.

Paper are solicited on, but not limited to the following topics:

  • Folksonomy
  • Tag Cloud
  • Taxonomy
  • Web 2.0
  • Ontology
  • Social Network
  • Semantic Web
  • Knowledge Discovery
  • Folksonomy-Based Knowledge Navigation
  • Folksonomy-Based Knowledge Retrieval
  • Folksonomy-Based Knowledge Searching
  • Folksonomy-Based Knowledge Visualization
  • Taxonomy Construction from Folksonomy
  • Taxonomy and Folksonomy Integration
  • Ontology and Folksonomy Integration

Paper Submission

Authors are invited to submit original and unpublished research papers. Paper submissions should be limited to a maximum of 8 pages in the Springer LNCS format. Please refer to the Springer LNCS web site for the paper formatting instructions. Preferred formats are Microsoft Word or PDF. Papers should be submitted via email to Professor Eric Tsui, the Workshop Chair. Papers submitted to the workshop will undergo a peer-review process. At least one author of the accepted paper is required to attend the workshop and present the paper.

Workshop Chairs

  • Dr. Eric Tsui, The Hong Kong Polytechnic University, Hong Kong (Chairman)
  • Dr. Kiu Ching Chieh, The Hong Kong Polytechnic University, Hong Kong

Workshop Committee

  • Kiu Ching Chieh, Hong Kong Polytechnic University, Hong Kong
  • Tanguy Coenen, Vrije Universiteit Brussel, Belgium
  • Celina Van Damme, Vrije Universiteit Brussel, Belgium
  • Martin Hepp, University of Innsbruck, Austria
  • Hak Lae Kim, National University of Ireland, Ireland
  • Dickson Lukose, MIMOS Berhad, Malaysia
  • Oge Marques, Florida Atlantic University, USA
  • Katharina Siorpaes, University of Innsbruck, Austria
  • Eric Tsui, Hong Kong Polytechnic University, Hong Kong


For more information on ITFEKN Workshop, contact Professor Eric Tsui at

Workshop 4:
Technologies for Knowledge Management

Short description of the workshop and its goals

While attempts to exactly define and explain terms such as knowledge and tacit still stir up much discussion, the practicalities of today's highly technical contexts require immediate technological solutions for Knowledge Management (KM).

This workshop's main goals are to gather researchers and practitioners to discuss the challenges, state of the art, and potential answers that technology can provide to solve KM problems. We are particularly interested in technological solutions that are enhanced with objective evaluations. Technology offers multiple opportunities to demonstrate a solution's effectiveness in contrast to many human-based solutions that are widely untested. Technological solutions can also solve problems that are essentially of human-oriented nature such as cultural problems, like expert locator systems and algorithms to identify collaborators.

Knowledge engineering (KE) is the field of study concerned with manipulating forms of computational knowledge into representations that computer systems can then use to reason with to solve problems. Although research in KE has much to offer to KM, in practice, most knowledge managers are still ignorant of its potential and benefits. We encourage any contributions that can help prevent redundant efforts and that can help merge the fields of KE and KM together towards jointly creating effective and efficient real world solutions.

Proposed workshop duration

This workshop is planned for a full-day. We expect to have at least three groups of submissions to include in three sessions of presentations, each session to be followed by a group discussion. We also plan to invite interested participants to co-author a paper describing workshop conclusions.

List of topics covered

The chairs welcome contributions on the use of principled technologies for performing any knowledge tasks such as knowledge sharing, leveraging, understanding, discovering; serving any communities such as inquiring organizations, communities of practice, communities of scientists.

We encourage submissions including methods that include, but are not limited to:

  • Ontologies
  • Case-based reasoning
  • Learning algorithms
  • Rule-based reasoning
  • Knowledge representation
  • Knowledge acquisition and elicitation
  • Knowledge modeling
  • Evaluation of KM systems
  • Technological solutions for cultural problems
  • Automated knowledge audits
  • Automated maintenance of KM systems
  • Automated manipulation an identification of knowledge artifacts with different purposes
  • Retrieval in repository-based systems

We encourage contributions that describe advances in these technological areas and also those that present important open questions for future research derived from practical applications. Exhaustive surveys that illustrate the benefits of use of technology for KM are also welcome.

Program committee

  • Bill Cheetham, GE Corporate Research Development, USA
  • Peter Funk, Malardalens University, Sweden
  • Sidath Gunawardena, Drexel University, USA (co-chair)
  • Michael M. Richter, Dept. of Computer Science, University of Calgary, Germany
  • Ian Watson, University of Auckland, New Zealand
  • Rosina Weber, Drexel University, USA (co-chair)

Description of workshop history

Although not part of a series, there were important workshops that have focused on closely related issues in the past, namely on synergies between technologies such as case-based reasoning and KM (AAAI-99 co-chairs David W. Aha et al.) and on intelligent lessons-learned systems (AAAI-2000 co-chairs David W. Aha and Rosina Weber).


Workshop 5:
Knowledge Management for Service Innovation

Short Description of the Workshop and Its Goals

Global economy has turned out to be a service-oriented economy, in addition to the fact that the economy is going along with more digitized information and knowledge. In Japan's case, for example, more than 70% of GDP has been created by service sectors recently, and the ratio is still going up. Furthermore, industry sectors are also getting into "servicizing" to create new additional values and cost reduction, not from product but from service relating to the product. The trend of the service-oriented economy would be the same in most of the countries worldwide.

However, the problem we are facing to the service-oriented economy emerges due to the uncertainness of service management and the low productivity of service businesses in general.

The purpose of this workshop is to discuss how to provide a solution or an insight to improve the situation as "service innovation", and to discuss framework and/or design process of service innovation working with knowledge management.

The goal of the workshop is to provide a common view of the knowledge management framework that will support service innovation for the service-oriented economy.

List of Topics Covered

  • Knowledge management concept (such as Polanyi's tacit knowing and Nonaka's SECI model) applying to service innovation
  • Methodologies for acquiring service-oriented knowledge
  • Measurement and indicators for service innovation
  • Measurement and indicators for small and medium size enterprises
  • Service scalability and service diversification
  • Analytical tools for knowledge and service management
  • Service innovation with Internet-based knowledge repository
  • Business models for knowledge and service management
  • Case studies for knowledge and service management
  • Globalization on service innovation
  • Commonalities and differences of product and service innovation

Workshop Chairs

  • Prof. Yoshinori Hara, Graduate School of Management, Kyoto University
  • Prof. Takahira Yamaguchi, Graduate School of Science and Technology, Keio University

Program Committee Members

  • Ulrich Geske, Fraunhofer Gesellschaft FIRST, Germany
  • Takayuki Ito, Nagoya Institute of Technology, Japan
  • Byeong-Ho KANG, University of Tasmania, Tasmania
  • Ulrich Reimer, University of Applied Sciences St. Gallen, Switzerland
  • Ryo Sato, University of Tsukuba, Japan
  • Ulrich Thiel, Fraunhofer Gesellschaft, Germany
  • Klaus Tochtermann, I-Know Center Graz, Austria
  • Eric Tsui, Hong Kong Polytechnic University, China
  • Mary-Anne Williams, University of Technology Sidney, Australia
  • Yoshinori Yamakawa, Kyoto University, Japan
  • Shuichiro Yamamoto, NTT Data, Japan
  • Michiko Yoshida, Fujitsu Research Institute, Japan


  • Prof. Yoshinori Hara:
  • Prof. Takahira Yamaguchi: