Development of interactive, human-centered automation should be built on theory and empirical research. To support the research & development processes systematically, a Socio-Cognitive Engineering (SCE) method was constructed for building, maintaining and re-using design knowledge based on the following principles:
- Creating human-centered automation is a multi-disciplinary collaborative activity
- Functional modules are defined and tested incrementally in an iterative refinement process
- Design decisions are explicitly based on claims analyses, explicating the up-downside tradeoffs
- Keeping and sharing the design rationale is key for progress and coherence in automation development
In an international project, the European Space Agency asked to establish a sound requirements baseline for a "Mission Execution Crew Assistant" (MECA) for future manned deep space missions (e.g. to Mars). As a concise method was lacking for the research & development of the envisioned human-automation system, a first version of the SCE methodology was constructed and applied. This methodology combines approaches from user-centered design, cognitive engineering and requirements analyses to establish a coherent "self-explaining" requirements baseline consisting of:
- The foundation that captures the relevant domain, human factors and technological knowledge.
- The specification of the objectives, use cases, functions (requirements) and the (expected) effects (claims).
- The evaluation that validates these claims and advances the foundation knowledge.