  Complex systems are not entirely decomposable, hence interdependences arise
at the interfaces in complex projects. When changes occur, significant risks
arise at these interfaces as it is hard to identify, manage and visualise the
systemic consequences of changes. Particularly problematic are the interfaces
in which there are multiple interdependencies, which occur where the boundaries
between design components, contracts and organisation coincide, such as between
design disciplines. In this paper, we propose an approach to digital twin-based
interface management, through an underpinning state-of-the-art review of the
existing technical literature and a small pilot to identify the characteristics
of future data-driven solutions. We set out an approach to digital twin-based
interface management and an agenda for research on advanced methodologies for
managing change in complex projects. This agenda includes the need to integrate
work on identifying systems interfaces, change propagation and visualisation,
and the potential to significantly extend the limitations of existing solutions
by using developments in the digital twin, such as linked data, semantic
enrichment, network analyses, natural language processing (NLP)-enhanced
ontology and machine learning.
