Expanding the semantic markup of wiki encyclopedias for transformation of protected content into learning objects for individual educational trajectories

Modern online encyclopedic resources provide actualization and integration of domain terminology, unambiguous definitions of its basic concepts and the semantics of relations between them agreed by experts. The use of encyclopedic content in the educational process allows to update the terminology of learning courses, correctly define connections with other disciplines and concepts, agree on definitions, etc. This content has to be protected from unauthorized changes, but as a result, third-party users do not have access to the elements of semantic structuring of such resources. Therefore, it is necessary to find a compromise between the resource code openness and the security of the encyclopedias content in order to expand their functionality and allow to obtain from them information pertinent for certain practical tasks. For this purpose, we propose to select clearly those elements of semantic markup that are necessary for search and further processing of the content of a certain type, to add these markup elements to pages of corresponding encyclopedic articles and formally define their values. We propose to expand the existing set of semantic properties, but display for users only a certain subset of the names and values of these properties. In this work, we consider this problem on example of metadata building for learning objects based on the transformation of the protected content of encyclopedic articles aimed at their use for the generation of individual educational trajectories. We have to define some minimal set of metadata that is sufficient for problem solving. For this purpose, we analyze the most common standards of metadata representation for learning objects and other important elements of the educational process. Based on this analysis, a set of properties of learning objects that can be obtained from the pertinent encyclopedia article (automatically, semi-automatically or with the help of domain experts) is selected.