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\section{Conclusion}  The software architecture and tool for creating the personal learning collections were designed and implemented within framework of proposed knowledge-based approach that uses developed the ontological model for knowledge representation including ontologies of learning course domain, learning resource, learner's profile and personal learning collection and SWRL reasoning rules for creating the collection itself.   Further evolution of the project implies implies:  \begin{itemize}  \item  reimplementation the collection builder as a web application using the Stardog Enterprise Graph Database as a data store and reasoning engine. Stardog is a fast SPARQL query answering, lightweight, transactional, with world class OWL 2 and SWRL reasoning support graph database and using it can improve the speed and scalability of the collection builder. Also builder;   \item implementation  the software tools tool as a web application  for creating the learning course ontologies and ontologies;  \item developing software tool as a web application for  annotating the learning resources, as well as the resources;  \item developing  ontologies for other university courses, should be developed. The courses;  \item the  learning resources repository (with Stardog backend as data store)  should be further scaled for subject domain of software engineering to provide the creation of personal collections for variety of learning courses. \end{itemize}