Research ingrastuctures for open science in social science research

Computational Social Science is a broad term that encompasses a variety of disciplines and methods. It covers a variety of aspects, from the usage of advanced technologies and large amount of data, to the focus on distributed dynamics of collective action. However, each declination of the term converges on the interdisciplinary effort this field requires and its role to understand the complexity of societies. The emergence of the discipline within the mainstream of the social sciences developed in parallel with the strengthening of the Open Science movement. Research infrastructures provide an essential support to Computational Social Science by enabling large-scale data curation and integration, offering research services, and promoting collaboration and training across diverse disciplines. This chapter describes how FOSSR can support this field as a meta-infrastructure, presenting some services and experiences related to the topic. The chapter is organized as follows. Section 17.2 provides an introduction to the field of Computational Social Science and delves into the benefits of research infrastructures to the discipline; Sect. 17.3 narrowsto the opportunities of FOSSR as a meta-infrastructure covering several aspects of Computational Social Science; Sect. 17.4 lists some detailed experiences and services in Computational Social Science research that were developed within the project, showing the potential usage and benefit for the field. Topics include Data Integration and Disambiguation, Knowledge Graphs, Agent-based Modeling and Multi-Agent Systems, Machine Learning, Network Science and Bayesian Networks. The chapter closes with the Conclusions in Sect. 17.5 where a synthesis of the case studies is provided to highlight the strategic role the FOSSR meta-infrastructure can have for Computational Social Science in the national context and beyond, delving also into reflections for sustainability of training of human capital.