researchers outside the intelligent and knowledge-based systems community have since highlighted the potential for DR to act as an explanatory knowledge base [14, 15, 18, 20]. These works point to the potential utility of DR as the basis for informed discussion between system designers and system users, and between designers and external stakeholders. Some have claimed that DR’s primary benefit is as a facilitator of this cross-party communication, rather than as a cognitive aid to designers or as a form of documentation, as it is often assumed .
DR helps to narrow the “gulf of understanding”  that exists between users who are domain experts and designers who understand how a particular system was intended to operate within a domain.
Prior research discussed in Sect. 2.3 highlights the potential for DR to improve the understanding of end users and other stakeholders external to the development team on a complex systems project. Despite this promise, relatively little work has empirically investigated this potential. In the sections that follow, I describe three condensed case studies that explore various aspects of these ideas. The first study was carried out with graduate student participants in a partially controlled environment. The second and third are field studies where DR was captured and is being used, in the first as a vehicle for a technology transfer and in the second as the basis for system evaluation and iterative redesign. The three cases reveal some of the challenges to harnessing the explanatory potential of DR, but also the opportunities for DR to contribute to the comprehensibility of complex systems.