Ricerc@Sapienza

In a context where digital giants are increasingly influencing the actions decided by public policies, smart data platforms are a tool for collecting a great deal of information on the territory and a means of producing effective public policies to meet contemporary challenges, improve the quality of the city, and create new services. Within the framework of the Smarter Together project, the cities of Lyon (France), Munich (Germany), and Vienna (Austria) have integrated this tool into their city’s metabolism and use it at different scales.

In an age where people flee from their countries of origin due to the worsening of conflicts and wars, of political crisis and violence, of terrorism, of religious radicalization processes, and persecutions, policy making needs to be based on a wider and more sensible information systems. Population censuses, sample surveys as well as administrative archives and registers are revealing some critical issues that could be partly overcome by the enormous informative potential offered by new sources and Big Data (Rango, 2014; De Backer, 2014).

In recent years, in all fields of knowledge, a data-driven approach has spread according to the new scenario defined by the Big Data era. The so-called data deluge has started a season where an impressive amount of data constitutes a valuable research material for scholars. In this new context, the data-driven approach enables academics and scientists to examine and organize data with the goal of increasing knowledge in many research areas. The deluge of data today allows us to plan new analyses on a variety of unstructured data that are produced in major part by web navigation.

The objective of this chapter is to address the following question: what is the value of the scientific networking, training and documentation activities in the new academic scenario dominated by the bibliometric assessment culture and by the impact of the technology to the science production and sharing (data-driven science, big data, open data, open access, etc.).

Obiettivo del presente lavoro è proporre un nuovo framework concettuale di governance basato su un approccio sistemico e tradotto in un modello generale per la gestione della conoscenza all’interno delle organizzazioni: la Smart Model-based governance. La finalità di questo modello è quella di superare i bias legati ai modelli di governo e di gestione della conoscenza tipici dei punti di vista esclusivamente procedurali oppure di quelli dichiarativi.

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein–protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks.