ИСТИНА

This paper presents the ways and the methods to build and populate the ontology, based on the taxonomy of the subject area, which can then be used to automate the learning processes. The applications include: analysis of educational and teaching activity of students and lecturers, contextual analysis and thematic search in big data systems, analysis of texts including the anti-plagiary protection, modeling the learning processes and generating various content such as teaching plans and tests. The ontology is composed of several parts. The built-in core part defines and describes the common notations, classes and relation types, which is compatible with the Dublin Core and synchronized with the international systems such as the Linking Open Data project. The dynamic part is populated by scientists and users working on different branches of science, using the ontology editor developed by the authors. The entered data is then combined together, and is used to form the unified semantic network of the scientific center. The core terms and relations in each branch of science are verified by experts on that branch. The ontology editor is built as part of ISTINA (Information System for Thematic Investigation of Scientometrical Data), the current research information system used in Lomonosov Moscow State University. It allows for entering the ontology data in multiple layers, such as modules, subjects, classes, terms and relations layers. Apart from the standalone mode, it also supports extracting the terms and relations from annotations entered to the ISTINA system and forming the suggestions for ontology parts to be added by the user.