Knowledge Engineering Practice And Patterns

Knowledge Engineering: Practice and Patterns

Knowledge Management and Knowledge Engineering is a fascinating ?eld of re- 1 search these days. In the beginning of EKAW , the modeling and acquisition of knowledge was the privilege of – or rather a burden for – a few knowledge engineers familiar with knowledge engineering paradigms and knowledge rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and allow for reusability, the knowledge models produced in these early days were typically used in single and very speci?c applications and rarely - changed. Moreover, these models were typically rather complex, and they could be understood only by a few expert knowledge engineers. This situation has changed radically in the last few years as clearly indicated by the following trends: – The creation of (even formal) knowledge is now becoming more and more collaborative. Collaborative ontology engineering tools and social software platforms show the potential to leverage the wisdom of the crowds (or at least of “the many”) to lead to broader consensus and thus produce shared models which qualify better for reuse. – A trend can also be observed towards developing and publishing small but 2 3 4 high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than complex and large knowledge models.

Knowledge Engineering: Practice and Patterns

Knowledge is considered as the most important asset in our modern society. It has now penetrated all facets of computing practice: from the rise of knowledge management to the Semantic Web and from the blog culture to the knowledge economy. This penetration has made proper knowledge engineering a most - quired feature. This volume contains the papers presented at the 16th International C- ference on Knowledge Engineering and Knowledge Management (EKAW 2008) held in Acitrezza, Sicily, Italy, September 29 to October 3 2008. EKAW 2008 is concerned with all aspects of eliciting, acquiring, modelling and managing knowledge, and their role in the construction of knowledge-intensive systems and services for the Semantic Web, knowledge management, e-business, natural language processing, intelligent integration information, etc. This year we paid special attention to the topic of “knowledge patterns” that can be considered as good practice or models that are applied or reused throughout the knowledge engineering life cycle. Hence, beyond traditional t- icsofEKAW,wesolicitedpapersthatcoverresearchonhowtodescribe,classify, model, extract and apply knowledge patterns in the design of ontologies, app- cations and products. We have paid special attention to the description of ex- riences that involve the application and identi?cation of knowledge patterns in social network analysis, natural language processing, multimedia analysis, p- tern recognition, etc.

Knowledge Engineering