The aim of this study is to design and implement a computer system, which will allow the semantic cataloging and data retrieval in the

field of cast iron processing. The intention is to let the system architecture allow for consideration of data on various processing techniques

based on the information available or searched by a potential user. This is achieved by separating the system code from the knowledge of

the processing operations or from the chemical composition of the material being processed. This is made possible by the creation and

subsequent use of formal knowledge representation in the form of ontology. So, any use of the system is associated with the use of

ontologies, either as an aid for the cataloging of new data, or as an indication of restrictions imposed on the data which draw user attention.

The use of formal knowledge representation also allows consideration of semantic meaning, a consequence of which may be, for example,

returning all elements in subclasses of the searched process class or material grade.

The problem of materials selection in terms of their mechanical properties during the design of new products is a key issue of design. The

complexity of this process is mainly due to a multitude of variants in the previously produced materials and the possibility of their further

processing improving the properties. In everyday practice, the problem is solved basing on expert or designer knowledge. The paper is the

proposition of a solution using computer-aided analysis of material experimental data, which may be acquired from external data sources.

In both cases, taking into account the rapid growth of data, additional tools become increasingly important, mainly those which offer

support for adding, viewing, and simple comparison of different experiments. In this paper, the use of formal knowledge representation in

the form of an ontology is proposed as a bridge between physical repositories of data in the form of files and user queries, which are

usually formulated in natural language. The number and the sophisticated internal structure of attributes or parameters that could be the

criteria of the search for the user are an important issue in the traditional data search tools. Ontology, as a formal representation of

knowledge, enables taking into account the known relationships between concepts in the field of cast iron, materials used and processing

techniques. This allows the user to receive support by searching the results of experiments that relate to a specific material or processing

treatment. Automatic presentation of the results which relate to similar materials or similar processing treatments is also possible, which

should make the conducted analysis of the selection of materials or processing treatments more comprehensive by including a wider range

of possible solutions.

Learning resources are massive, heterogeneous, and constantly changing. How to find the required resources quickly and accurately has become a very challenging work in the management and sharing of learning resources. According to the characteristics of learning resources, this paper proposes a progressive learning resource description model, which can describe dynamic heterogeneous resource information on a fine-grained level by using information extraction technology, then a semantic annotation algorithm is defined to calculate the semantic of learning resource and add these semantic to the description model. Moreover, a semantic search method is proposed to find the required resources, which calculate the content with the highest similarity to the user query, and then return the results in descending order of similarity. The simulation results show that the method is feasible and effective.