KnowWE: a Semantic Wiki for knowledge engineering

Joachim Baumeister, Jochen Reutelshoefer, Frank Puppe
2010 Applied intelligence (Boston)  
Recently, Semantic Wikis showed reasonable success as collaboration platforms in the context of social semantic applications. In this paper, we present a novel approach, that interprets the concept of Semantic Wikis as a knowledge engineering environment, that effectively help to build decision-support systems. We introduce the Semantic Wiki KnowWE, that provides the possibility to define and maintain ontologies together with strong problemsolving knowledge. Thus, the wiki can be used to
more » ... ratively build decision-support systems. These enhancements require extensions of the standard Semantic Wiki architecture by a task ontology for problem-solving and an adapted reasoning process. We discuss these extensions in detail, and we describe a case study in the field of medical emergency systems. Keywords knowledge acquisition · knowledge engineering tools · decision-support systems Introduction In the last decades, the application of intelligent decision-support systems showed their advantages in many domains-examples of successful uses are described in the literature [13, 26, 28, 33, 35] . When building such systems, the most critical challenge is the development and maintenance of the knowledge bases. In the past, this challenge has been primarily tackled by the introduction of comprehensive methodologies describing the structured construction and application of the knowledge; examples are CommonKADS [50], the On-To-Knowledge Methodology [54] , DILIGENT [55], and the Agile Methodology [12] . Corresponding tools are often tailored to the specific methodologies, and they usually limit the developer to a specific knowledge representation to be applied when building the system, for example Protégé [39, 22] , OntoEdit [53], and KnowME [2, 4] . Today's knowledge engineering projects, however, often face the challenge that knowledge is present at different levels of formalization. Knowledge appears in different representations ranging from technical documents, construction plans, sheets, and experiences of human experts, but also in the explicit form of rules and models. Moreover, we see that
doi:10.1007/s10489-010-0224-5 fatcat:puxqyp7nn5ditfa5pgqmw3xij4