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\section{Software Architecture. Implementation Aspects}  To create the personal learning collections using the proposed ontologies and method, it is necessary to use appropriate software tools, providing the logic reasoning on ontologies (reasoning engines). To implement the logical reasoning the reasoning engine RacerPro (Racer Systems GmbH and Co. KG, Germany) was used. This engine supports the ontologies described with OWL language and reasoning rules described in SWRL. It also can work as server with both DIG (DL Implementors Group) interface and TCP/IP interface with internal queries language nRQL. DIG is a application interface to interact with the reasoning engine that also allows to work with OWL-ontologies and interact with other software tools like ontologies editor Protégé. However this interface has some restrictions, including impossibility to work with SWRL reasoning rules, so the TCP/IP interface was used to implement the SWRL-reasoning.   RacerPro (Fig. \ref{fig:racer}) позволяет загружать предметные онтологии и описания объектов на основе онтологических моделей в формате allows to load ontologies and ontology-based annotations in  OWL (1-5), которые могут также включать правила в формате SWRL. Модуль построения ЭОК взаимодействует с RacerPro, генерируя запросы на загрузку owl-файлов, проведение логического вывода и запросы на языке nRQL к результирующей онтологии (7), получая соответствующие результаты (1-5) - Learning course domain ontology, Learning resource ontology, Learner profile ontology, Personal learning collection ontology, resources annotations within Learning resources repository - that can also include SWRL reasoning rules. Personal collection builder module interacts with the RacerPro reasoning engine, it generates requests for the OWL files load, forward chaining reasoning and nRQL-request for the ontology (7) and gets back the corresponding results from the RacerPro  (6). На основе обработки результатов, полученных от RacerPro, модуль построения ЭОК формирует представление персонифицированной ЭОК для пользователя On the base of the received results the Personal collection builder generates the learning resources presentation for the learner as the Personal learning collection  (8) and provides the ability for learning management on this collection.