Decision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones), the best recognized and successfully used in practice represented by expert systems. The knowledge indispensable for such systems to perform inference is most frequently acquired directly from experts (through a dialogue: a domain expert - a knowledge engineer) and from various source documents. Little is known, however, about the possibility of automating knowledge acquisition in this area and as a result, in practice it is scarcely ever used. lt has to be noted that in numerous areas of management more and more attention is paid to the issue of acquiring knowledge from available data. What is known and successfully employed in the practice of aiding the decision-making is the different methods and tools. The paper attempts to select methods for knowledge discovery in data and presents possible ways of representing the acquired knowledge as well as sample tools (including programming ones), allowing for the use of this knowledge in the area under consideration.
The paper presents a new ontology-based approach to the elaboration and management of evidences prepared by developers for the IT security evaluation process according to the Common Criteria standard. The evidences concern the claimed EAL (Evaluation Assurance Level) for a developed IT product or system, called TOE (Target of Evaluation), and depend on the TOE features and its development environment. Evidences should be prepared for the broad range of IT products and systems requiring assurance. The selected issues concerning the author’s elaborated ontology are discussed, such as: ontology domain and scope definition, identification of terms within the domain, identification of the hierarchy of classes and their properties, creation of instances, and an ontology validation process. This work is aimed at the development of a prototype of a knowledge base representing patterns for evidences.