Knowledge bases are encountered in AI areas such as configuration, planning, diagnosis, semantic web, game playing, and others. Very often the amount and arrangement of the elements in the knowledge base outstrips the capability of a knowledge engineer to survey them and to effectively perform extension and maintenance operations - a situation that triggers an enormous demand to extend and improve existing development and maintenance practices. This demand is further boosted by emerging Social Semantic Web applications that require the support of distributed engineering scenarios. Intelligent development and maintenance approaches are of high relevance and have attracted lasting research and interest from industrial partners. This is demonstrated by numerous publications, for example, in the IJCAI, AAAI, ECAI, KCAP, CP, IUI, and ISWC conference and workshop series. The major goal of this workshop on “Intelligent Engineering Techniques for Knowledge Bases” is to act as a platform for the presentation and discussion of novel and innovative research and to introduce new application domains. Topics of interest include but are not limited to:

* (collaborative) knowledge base development & maintenance
* knowledge base testing
* automated knowledge base debugging and repair
* intelligent knowledge visualization
* complexity metrics in knowledge base development
* refactoring of knowledge bases
* knowledge engineering environments
* knowledge representations for configurable products & services
* product & service knowledge bases in the semantic web
* (collaborative) ontology development
* ontology alignment / matching
* semantic wiki based knowledge engineering
* recommendation and retrieval of ontologies
* empirical and case studies