Abstract

The term “Big Data” has recently become mainstream, especially thanks to the ease in sharing and producing data: think, for example, of open-source repository infrastructures of scientific or genetic data or of data collected through social media platforms. This gives rise to a substantial increase in the available data in all scientific fields, including social and behavioral sciences. The possibility of combining data from various sources promotes new chances of knowledge by allowing, as never before, to deeply analyze multiple interrelationships, across measures and variables. This is of particular interest in the social sciences where multiple domains and factors need to be evaluated and interpreted simultaneously. However, if on the one hand, the availability of large amount of data opens interesting scenarios for new applications and analyses, on the other hand, it gives rise to new challenges regarding the management and the analysis of these complex data. In such a context, expertise in research design and in statistical analysis becomes crucial to produce high quality scientific research.