ABSTRACT
This chapter discusses the challenges that are imposed by big data on the modern and future e-scientific data infrastructure (SDI). It also discusses the nature and definition of big data, including characteristics as volume, velocity, variety, value, and veracity. The chapter explains different scientific communities to define requirements on data management, access control, and security. It introduces the scientific data life cycle management (SDLM) model, which includes all the major stages and reflects specifics in data management in modern e-science. The chapter proposes the generic SDI architectural model that provides a basis for building interoperable data or project-centric SDI using modern technologies and best practices. It describes how the proposed models SDLM and SDI can be naturally implemented using modern cloud-based infrastructure services and analyses security and trust issues in cloud-based infrastructure and summarizes requirements to access control and access control infrastructure that should allow secure and trusted operation and use of the SDI.
