Based on the first RISIS project from 2014-2018, RISIS goes on given the high interest on RISIS datasets and their integration. RISIS2 has started in 2019 and provides ongoing access to the existing RISIS datasets:

RISIS2 Project Website

The SMS platform and the data store remain accessible:

SMS Platform

This project is funded by the European Union under the Seventh Framework Programme Grant Agreement n°313082
European Union

Updates August 2017: 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.

The SMS platform now interlinks more than 50 heterogeneous datasets in the STI domain (see the complete list here), based on an entity-centric approach. The following entity types are extracted after analysis of the existing RISIS datasets and their related open datasets: Funding Programs, Projects, Publications, Patents, Persons, Organizations, Organization Rankings, Geo locations, Geo boundaries and Geo statistical data. It is also possible to add new entity types based on the research questions which need to be answered by the SMS infrastructure. The main idea is creating a data network by linking and enriching the data, a network which the social science user can access through the faceted browser. By selecting the required entities and properties from the data network, the user gets an overview of the data he/she is interested in. The platform produces in the background the required SPARQL queries to retrieve the selected data from multiple datasets in a required format for further analysis.

Data Curation, Semantic Enrichment of Data, Data Linking, Browsing and Querying Data are some of the tasks currently supported in the SMS platform.

+ Apply for a visit to SMS dataset

+ Check SMS tutorials on Youtube

+ Check more info about the SMS platform: