Engaging Practitioners within Design Science Research: A Natural Language Processing Case Study

Using domain knowledge to instruct domain specific Natural Language Processing (NLP) applications requires that knowledge intensive design challenges associated with developing extraction rules and conceptual models from that knowledge be addressed. Applying the nested problem-driven approach of Design Science Research (DSR) assists knowledge problem reduction to practical problems, delivering artifacts of utility. Where artifact design has to facilitate practitioner and research stakeholder expectations, dual leveraging of design process stages and conceived artifacts is required. This paper presents how an existing Information Systems (IS) framework, previously applied to enterprise architecture research, can be adapted to enhance stakeholder engagement within a collaborative informatics research project. The business motivation behind domain specific NLP is explained and design challenges encountered in framework application to use case development, discussed. Further contributions that outline artifact evolution using problem decomposition are made through integrating expert domain knowledge and design knowledge translation as part of the adapted research process.