OBSERVING ODOR-RELATED INFORMATION IN ACADEMIC DOMAIN

In this paper, we demonstrate an approach for observing olfactory related information in an academic publications environment (such as Microsoft Academic Graph) based on semantic technologies. We present an Odor Observatory tool that enables several usage scenarios, such as observing odor-related papers and topics, viewing institutions conducting olfactory research, defining top journals and key countries in the olfactory domain. Validation of the proposed approach on a collection of academic publications from 1800 until 1925 confirms applicability of the proposed approach on large data collections with a wide span of time. In usage scenarios we observed the odor-related publications in Microsoft Academic Graph by topic, discovered the journals with historical olfactory publications and found that the most popular terms in odor-related research content are: method, olfactory, odor, device, invention, smell, preparation, utility model.