Disciplinary Convergence

Abstract

The fast-developing intelligent infrastructure landscape catalyzes transformative new relationships of human, technology, and environment and requires new socio-technical configurations of information practice and knowledge work. With a focus on data as the source of intelligence, this paper aims to explore the shifting scenarios and indicative features of data science solutions for intelligent system applications and identify the evolving knowledge spaces and integrative learning practices in the “smart” landscape. It projects and discusses the democratization of data science platforms, the distribution of data intelligence on the edge, and the transition from vertical to horizontal data solutions in solving intelligent system problems. Through mapping the changing data research landscape, this work further reveals essential new roles of knowledge architects and social engineers in enabling dynamic data linking, interaction, and exploration for transdisciplinary data convergence.