Guillem Rull

Enric Fuster, Tatiana Fernández, Hermes Carretero et al.

In the new research and innovation (R&I) paradigm, aimed at a transformation towards more sustainable, inclusive and fair pathways to address societal and environmental challenges, and at generating new patterns of specialisation and new trajectories for socioeconomic development, it is essential to provide monitoring systems and tools to map and understand the contribution of R&I policies and projects. To address this transformation, we present the RIS3-MCAT platform, the result of a line of work aimed at exploring the potential of open data, semantic analysis, and data visualisation, for monitoring challenge-oriented smart specialisation in Catalonia. RIS3-MCAT is an interactive platform that facilitates access to R&I project data in formats that allow for sophisticated analyses of a large volume of texts, enabling the detailed study of thematic specialisations and challenges beyond classical classification systems. Its conceptualisation, development framework and use are presented in this paper.

Sihem Amer-Yahia, Georgia Koutrika, Frederic Bastian et al.

A full-fledged data exploration system must combine different access modalities with a powerful concept of guiding the user in the exploration process, by being reactive and anticipative both for data discovery and for data linking. Such systems are a real opportunity for our community to cater to users with different domain and data science expertise. We introduce INODE -- an end-to-end data exploration system -- that leverages, on the one hand, Machine Learning and, on the other hand, semantics for the purpose of Data Management (DM). Our vision is to develop a classic unified, comprehensive platform that provides extensive access to open datasets, and we demonstrate it in three significant use cases in the fields of Cancer Biomarker Reearch, Research and Innovation Policy Making, and Astrophysics. INODE offers sustainable services in (a) data modeling and linking, (b) integrated query processing using natural language, (c) guidance, and (d) data exploration through visualization, thus facilitating the user in discovering new insights. We demonstrate that our system is uniquely accessible to a wide range of users from larger scientific communities to the public. Finally, we briefly illustrate how this work paves the way for new research opportunities in DM.