  Near-Earth space continues to be the focus of critical services and
capabilities provided to the society. With the steady increase of space
traffic, the number of Resident Space Objects (RSOs) has recently boomed in the
context of growing concern due to space debris. The need of a holistic and
unified approach for addressing orbital collisions, assess the global in-orbit
risk, and define sustainable practices for space traffic management has emerged
as a major societal challenge. Here, we introduce and discuss a versatile
framework rooted on the use of the complex network paradigm to introduce a
novel risk index for space sustainability criteria. With an entirely
data-driven, but flexible, formulation, we introduce the Resident Space Object
Network (RSONet) by connecting RSOs that experience near-collisions events over
a finite-time window. The structural collisional properties of RSOs are thus
encoded into the RSONet and analysed with the tools of network science. We
formulate a geometrical index highlighting the key role of specific RSOs in
building up the risk of collisions with respect to the rest of the population.
Practical applications based on Two-Line Elements and Conjunction Data Message
databases are presented.
