Innovation activity data processing and aggregation based on ontological modelling

Innovation capacity building plays a central role in the growth dynamics of successful developing countries. However, no dedicated studies on ontological modeling of economic processes related to innovative activity at macro level were found. The application of semantic web technologies enables a unified, flexible structure and integrates not only quantitative but, more importantly, qualitative indicators and creates conditions for machine processing in the future. This paper presents the rationale for the selected domain modeling method for the subsequent construction of automated search information system; the ontology for innovative activity and economic potential is developed in context of the RF macroeconomics. An approach and search algorithms for economic data sources and data collection were developed under this study and casting data to the ontology structure of innovative activity and economic potential was performed. The relevance and scientific novelty of the study is determined by the problem domain, as well as the application of semantic web technologies to data collection from distributed heterogeneous sources, including those semi-structured and unstructured.