Health Data Science

HEAD: Emanuele Di Angelantonio

The Centre for Health Data Science aims to become a reference institution for the analysis of healthcare data. It will collect data and information from a variety of sources by establishing a dialogue with regional healthcare districts, hospitals and scientific societies. The Centre will integrate clinical data with socioeconomic and environmental risk factors to identify precise vulnerability profiles in order to create targeted policy interventions. In addition, it will work to develop solutions for the analysis of data, developing and integrating new analytical methods with clinical epidemiology and healthcare research.

Centre members

Steering Committee


  • 09/2019

    Methods to account for citation inflation in research evaluation

    Quantitative research evaluation requires measures that are transparent, relatively simple, and free of disciplinary and temporal bias. We document and provide a solution to a hitherto unaddressed temporal bias – citation inflation – which arises from the basic fact that scientific publication is steadily growing at roughly 4% per year. Moreover, because the total production […]

  • 08/2019

    Communities and regularities in the behaviour of investment fund managers

    We analyze a large microlevel dataset on the full daily portfolio holdings and exposures of 22 complex investment funds to shed light on the behavior of professional investment fund managers. We introduce a set of quantitative attributes that capture essential distinctive features of manager allocation strategies and behaviors. These characteristics include turnover, attitude toward hedging, […]

  • 06/2019

    Better to stay apart: asset commonality, bipartite network centrality, and investment strategies

    By exploiting a bipartite network representation of the relationships between mutual funds and portfolio holdings, we propose an indicator that we derive from the analysis of the network, labelled the Average Commonality Coefficient (ACC), which measures how frequently the assets in the fund portfolio are present in the portfolios of the other funds of the […]

  • 05/2019

    Turning big data into smart data: two examples based on the analysis of the Mappa dei Rischi dei Comuni Italiani

    The recently presented Mappa dei Rischi dei Comuni Italiani is a freely accessible web portal, implemented by ISTAT, which provides integrated data on different natural risks in Italian municipalities together with socio-economic and demographic data We here illustrate two paradigmatic examples where the big data of the Mappa are transformed into smart data using advanced […]

  • 05/2019 - Journal of Informetrics

    Long-term correlations in short, non-stationary time series: An application to international R&D collaborations

    Within the perimeter of patent collaboration networks, the average distance of collaborations and the number of countries involved per each collaboration have been shown to have increased steadily in time. Less attention, though, has been devoted to assessing whether this growth of cross-country collaborations is stable in time. To address this scientific question we focus […]