Semantically Mapping Science (SMS) Platform

Up to now, STI (Science, Technology, Innovation) studies are either rich but small scale (qualitative case studies) or large scale and under-complex – because they generally use only a single dataset like Patstat, Scopus, WoS (Web of Science), OECD STI indicators, etc., and therefore deploying only a few variables – determined by the data available. However, progress in the STI research field (and the social sciences in general) depends in our view on the ability to do large-scale studies with often many variables specified by relevant theories. There is a need for studies which are at the same time big and rich. The aim of the Semantically Mapping Science (SMS) platform is to enable enriching and integration of heterogeneous data, ranging from tabular statistical data to unstructured data found on the Web, in order to exploit the huge amount of data that are ‘out there’ in an innovative and meaningful way.