ИСТИНА

The paper discloses an innovative approach to identify global and national priorities of agricultural technologies development, relying on big data analysis, namely text mining augmented by syntactic analysis techniques. The analysis is based on ontology of currently emerging and globally spreading agriculture-related technologies derived from the large array of documents. The process of development of the selected technologies was decomposed in geographic order describing their diffusion patterns in different countries taking into account sub-sectoral and national particularities. The sources for the analysis were heterogeneous and include some 14 million research papers, patent applications with both full-text data and additional structured metadata, analytical reports by main international organizations and national key players, media and news resources. The tools developed for the analysis enable large-scale collection, extraction and processing of data relevant to agriculture. The results are visualized through semantic charts, or automatically generated ontologies, geographical maps and co-occurrence matrix matching technologies with countries. Thus, the most relevant topics within the studied data and their inter-relationships in geographic context are revealed, and an extensive and an objective snapshot of spatial dynamics of innovation processes in agriculture obtained.