Abstract
In the context of scientific investigations, data have acquired an ever growing leading role while their large scale, cross-community and cross-domain sharing have concurred to identify new investigation paradigms (Hey, Tansley, & Tolle, 2009). Unfortunately, data interoperability – a mandatory prerequisite for achieving the above scenarios – is still a difficult open research challenge. Both the “data” and “interoperability” concepts are difficult to be fully perceived and actually lead to different perceptions in diverse communities. This problem is further amplified when considered in the context of (global) research data infrastructures that are expected to serve a plethora of communities of practice (Lave & Wenger, 1991) potentially involved in very diverse application scenarios, each characterised by a specific sharing problem.