  Scientific communities naturally tend to organize around data ecosystems
created by the combination of their observational devices, their data
repositories, and the workflows essential to carry their research from
observation to discovery. However, these legacy data ecosystems are now
breaking down under the pressure of the exponential growth in the volume and
velocity of these workflows, which are further complicated by the need to
integrate the highly data intensive methods of the Artificial Intelligence
revolution. Enabling ground breaking science that makes full use of this new,
data saturated research environment will require distributed systems that
support dramatically improved resource sharing, workflow portability and
composability, and data ecosystem convergence.
  The Cybercosm vision presented in this white paper describes a radically
different approach to the architecture of distributed systems for
data-intensive science and its application workflows. As opposed to traditional
models that restrict interoperability by hiving off storage, networking, and
computing resources in separate technology silos, Cybercosm defines a minimally
sufficient hypervisor as a spanning layer for its data plane that virtualizes
and converges the local resources of the system's nodes in a fully
interoperable manner. By building on a common, universal interface into which
the problems that infect today's data-intensive workflows can be decomposed and
attacked, Cybercosm aims to support scalable, portable and composable workflows
that span and merge the distributed data ecosystems that characterize leading
edge research communities today.
