Advances in artificial intelligence sensor computing robotics and mobile systems are making
autonomous systems a reality. At the same time the influence of edge computing is leading to
more distributed architectures incorporating more autonomous elements. The flow of information
is critical in such environments but the real time distributed nature of the system
components complicates the data protection mechanisms. Policy-based management has proven
useful in simplifying the complexity of management in domains like networking security and
storage it is expected that many of those benefits would carry over to the task of managing
big data and autonomous systems. This book aims at providing an overview of recent work and
identifying challenges related to the design of policy-based approaches for managing big data
and autonomous systems. An important new direction explored in the book is to make the major
elements of the system self-describing and self-managing. This would lead to architectures
where policy mechanisms are tightly coupled with the system elements. In such integrated
architectures we need new models for information assurance traceability of information and
better provenance on information flows. In addition when dealing with devices with actuation
capabilities and thus being able to make changes to physical spaces safety is critical. With
an emphasis on policy-based mechanisms for governance of data security and privacy and for
safety assurance the papers in this volume follow three broad themes: foundational principles
and use-cases for the autonomous generation of policies safe autonomy policies and autonomy
in federated environments.
